Michael I. Jordan | Academic Influence

Michael I. Jordan's AcademicInfluence.com Rankings

Michael I. Jordan

Computer Science

#36

World Rank

#38

Historical Rank

#20

USA Rank

Machine Learning

#1

World Rank

#1

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#1

USA Rank

Distributed Computing

#1

World Rank

#1

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#1

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Algorithms

#7

World Rank

#7

Historical Rank

#2

USA Rank

computer-science Degrees

Michael I. Jordan

Mathematics

#280

World Rank

#602

Historical Rank

#132

USA Rank

Statistics

#9

World Rank

#15

Historical Rank

#5

USA Rank

Measure Theory

#11

World Rank

#27

Historical Rank

#3

USA Rank

mathematics Degrees

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Computer Science
Mathematics

Michael I. Jordan's Degrees

PhD Computer Science University of California, San Diego
Masters Mathematics Arizona State University
Bachelors Psychology Louisiana State University

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Why Is Michael I. Jordan Influential?

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According to Wikipedia, Michael Irwin Jordan is an American scientist, professor at the University of California, Berkeley and researcher in machine learning, statistics, and artificial intelligence. Jordan was elected a member of the National Academy of Engineering in 2010 for contributions to the foundations and applications of machine learning.

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Michael I. Jordan's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Latent Dirichlet Allocation (2001) (34032)
On Spectral Clustering: Analysis and an algorithm (2001) (9137)
Trust Region Policy Optimization (2015) (4825)
Adaptive Mixtures of Local Experts (1991) (4293)
Graphical Models, Exponential Families, and Variational Inference (2008) (4169)
An Introduction to Variational Methods for Graphical Models (1999) (4081)
GRAPHICAL MODELS (1998) (4033)
Machine learning: Trends, perspectives, and prospects (2015) (3927)
Hierarchical Dirichlet Processes (2006) (3732)
Learning Transferable Features with Deep Adaptation Networks (2015) (3679)
Distance Metric Learning with Application to Clustering with Side-Information (2002) (3206)
An internal model for sensorimotor integration. (1995) (3104)
Hierarchical Mixtures of Experts and the EM Algorithm (1993) (3071)
Optimal feedback control as a theory of motor coordination (2002) (2736)
Learning the Kernel Matrix with Semidefinite Programming (2002) (2557)
An Introduction to MCMC for Machine Learning (2004) (2502)
On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes (2001) (2361)
Active Learning with Statistical Models (1996) (2212)
High-Dimensional Continuous Control Using Generalized Advantage Estimation (2015) (2133)
Loopy Belief Propagation for Approximate Inference: An Empirical Study (1999) (1841)
Kernel independent component analysis (2003) (1841)
Matching Words and Pictures (2003) (1797)
Kalman filtering with intermittent observations (2004) (1717)
Deep Transfer Learning with Joint Adaptation Networks (2016) (1683)
Forward Models: Supervised Learning with a Distal Teacher (1992) (1655)
Multiple kernel learning, conic duality, and the SMO algorithm (2004) (1641)
Theoretically Principled Trade-off between Robustness and Accuracy (2019) (1505)
Variational inference for Dirichlet process mixtures (2006) (1412)
Variational inference for Dirichlet process mixtures (2006) (1412)
Learning in Graphical Models (1999) (1354)
Convexity, Classification, and Risk Bounds (2006) (1297)
Conditional Adversarial Domain Adaptation (2017) (1296)
Factorial Hidden Markov Models (1995) (1249)
Modeling annotated data (2003) (1248)
Unsupervised Domain Adaptation with Residual Transfer Networks (2016) (1200)
Convex and Semi-Nonnegative Matrix Factorizations (2010) (1157)
Attractor dynamics and parallelism in a connectionist sequential machine (1990) (1130)
Hierarchical Topic Models and the Nested Chinese Restaurant Process (2003) (1120)
A Direct Formulation for Sparse Pca Using Semidefinite Programming (2004) (1014)
Serial Order: A Parallel Distributed Processing Approach (1997) (980)
On the Convergence of Stochastic Iterative Dynamic Programming Algorithms (1993) (937)
Detecting large-scale system problems by mining console logs (2009) (902)
Scalable statistical bug isolation (2005) (864)
On Convergence Properties of the EM Algorithm for Gaussian Mixtures (1996) (856)
Deep Generative Modeling for Single-cell Transcriptomics (2018) (833)
Local privacy and statistical minimax rates (2013) (782)
Kalman filtering with intermittent observations (2003) (752)
A statistical framework for genomic data fusion (2004) (746)
Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces (2004) (733)
Feature selection for high-dimensional genomic microarray data (2001) (724)
Ray: A Distributed Framework for Emerging AI Applications (2017) (722)
Learning with Mixtures of Trees (2001) (716)
How to Escape Saddle Points Efficiently (2017) (681)
Supervised learning from incomplete data via an EM approach (1993) (673)
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies (2007) (667)
Sensorimotor adaptation in speech production. (1998) (660)
Managing data transfers in computer clusters with orchestra (2011) (629)
Bug isolation via remote program sampling (2003) (626)
Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization (2008) (625)
Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks (1990) (615)
Bayesian parameter estimation via variational methods (2000) (610)
Learning Dependency-Based Compositional Semantics (2011) (590)
Is Q-learning Provably Efficient? (2018) (580)
Joint covariate selection and joint subspace selection for multiple classification problems (2010) (539)
Gradient Descent Only Converges to Minimizers (2016) (517)
Learning Spectral Clustering (2003) (516)
RLlib: Abstractions for Distributed Reinforcement Learning (2017) (508)
A Robust Minimax Approach to Classification (2003) (508)
A Probabilistic Interpretation of Canonical Correlation Analysis (2005) (497)
PEGASUS: A policy search method for large MDPs and POMDPs (2000) (494)
The Constrained Laplacian Rank Algorithm for Graph-Based Clustering (2016) (489)
Chemogenomic profiling: identifying the functional interactions of small molecules in yeast. (2004) (488)
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes (2004) (487)
Fast approximate spectral clustering (2009) (474)
A variational perspective on accelerated methods in optimization (2016) (467)
Mean Field Theory for Sigmoid Belief Networks (1996) (458)
Hierarchical Beta Processes and the Indian Buffet Process (2007) (452)
Provably Efficient Reinforcement Learning with Linear Function Approximation (2019) (447)
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification (2008) (444)
Variational Bayesian Inference with Stochastic Search (2012) (433)
Learning Without State-Estimation in Partially Observable Markovian Decision Processes (1994) (430)
Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems (1994) (427)
Nonparametric Latent Feature Models for Link Prediction (2009) (420)
Bridging Theory and Algorithm for Domain Adaptation (2019) (418)
Failure diagnosis using decision trees (2004) (392)
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation (2018) (384)
Reinforcement Learning with Soft State Aggregation (1994) (367)
A scalable bootstrap for massive data (2011) (360)
A Kernelized Stein Discrepancy for Goodness-of-fit Tests (2016) (360)
Autonomous Helicopter Flight via Reinforcement Learning (2003) (359)
Revisiting k-means: New Algorithms via Bayesian Nonparametrics (2011) (356)
Kernel-Based Data Fusion and Its Application to Protein Function Prediction in Yeast (2003) (355)
MLbase: A Distributed Machine-learning System (2013) (350)
A Sticky HDP-HMM With Application to Speaker Diarization (2009) (348)
Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations (2013) (343)
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack (2019) (339)
Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing (2014) (334)
SUPPORT UNION RECOVERY IN HIGH-DIMENSIONAL MULTIVARIATE REGRESSION (2008) (334)
Probabilistic Independence Networks for Hidden Markov Probability Models (1997) (332)
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems (2019) (328)
Convergence results for the EM approach to mixtures of experts architectures (1995) (326)
Communication-Efficient Distributed Dual Coordinate Ascent (2014) (326)
Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning (2009) (321)
Learning Semantic Correspondences with Less Supervision (2009) (320)
Partial Transfer Learning with Selective Adversarial Networks (2017) (317)
Are arm trajectories planned in kinematic or dynamic coordinates? An adaptation study (1995) (315)
Hierarchical Bayesian Nonparametric Models with Applications (2008) (313)
Streaming Variational Bayes (2013) (313)
A mantle plume below the Eifel volcanic fields, Germany (2001) (311)
Stable algorithms for link analysis (2001) (310)
Exploiting Tractable Substructures in Intractable Networks (1995) (304)
An HDP-HMM for systems with state persistence (2008) (301)
Transferable Representation Learning with Deep Adaptation Networks (2019) (301)
Learning Spectral Clustering, With Application To Speech Separation (2006) (298)
Kernel dimension reduction in regression (2009) (298)
Minimax Optimal Procedures for Locally Private Estimation (2016) (285)
An Alternative Model for Mixtures of Experts (1994) (278)
Communication-Efficient Distributed Statistical Inference (2016) (274)
Privacy Aware Learning (2012) (270)
A critical assessment of Mus musculus gene function prediction using integrated genomic evidence (2008) (261)
Link Analysis, Eigenvectors and Stability (2001) (253)
Predictive low-rank decomposition for kernel methods (2005) (252)
Universal Domain Adaptation (2019) (250)
Smoothness maximization along a predefined path accurately predicts the speed profiles of complex arm movements. (1998) (250)
Semiparametric latent factor models (2005) (249)
A General Analysis of the Convergence of ADMM (2015) (246)
Information-theoretic lower bounds for distributed statistical estimation with communication constraints (2013) (240)
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification (2018) (239)
A generalized mean field algorithm for variational inference in exponential families (2002) (239)
Statistical Machine Learning Makes Automatic Control Practical for Internet Datacenters (2009) (236)
Bayesian Nonparametrics: Hierarchical Bayesian nonparametric models with applications (2010) (231)
Sensorimotor adaptation of speech I: Compensation and adaptation. (2002) (231)
Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent (2017) (229)
Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization (2007) (229)
A Lyapunov Analysis of Momentum Methods in Optimization (2016) (227)
Characterizing, modeling, and generating workload spikes for stateful services (2010) (227)
CoCoA: A General Framework for Communication-Efficient Distributed Optimization (2016) (226)
A variational approach to Bayesian logistic regression problems and their extensions (1996) (224)
A more biologically plausible learning rule for neural networks. (1991) (223)
Underdamped Langevin MCMC: A non-asymptotic analysis (2017) (222)
Loopy Belief Propogation and Gibbs Measures (2002) (221)
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems (2008) (219)
Particle gibbs with ancestor sampling (2014) (219)
Bayesian Nonparametric Inference of Switching Dynamic Linear Models (2010) (218)
What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization? (2019) (216)
The Infinite PCFG Using Hierarchical Dirichlet Processes (2007) (213)
Learning from Incomplete Data (1994) (213)
Gradient Descent Can Take Exponential Time to Escape Saddle Points (2017) (212)
In-Network PCA and Anomaly Detection (2006) (208)
Non-convex Finite-Sum Optimization Via SCSG Methods (2017) (207)
Surface/surface intersection (1987) (207)
Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes (2008) (206)
Protein Molecular Function Prediction by Bayesian Phylogenomics (2005) (205)
Computational and statistical tradeoffs via convex relaxation (2012) (205)
Supervised learning and systems with excess degrees of freedom (1988) (204)
A kernel-based learning approach to ad hoc sensor network localization (2005) (204)
Generalization to Local Remappings of the Visuomotor Coordinate Transformation (1996) (204)
Gradient Descent Converges to Minimizers (2016) (200)
Genomic privacy and limits of individual detection in a pool (2009) (200)
Divide-and-Conquer Matrix Factorization (2011) (199)
Learning piecewise control strategies in a modular neural network architecture (1993) (196)
MLI: An API for Distributed Machine Learning (2013) (196)
Perturbed Iterate Analysis for Asynchronous Stochastic Optimization (2015) (196)
A Linearly-Convergent Stochastic L-BFGS Algorithm (2015) (193)
Nested Hierarchical Dirichlet Processes (2012) (192)
Variational Probabilistic Inference and the QMR-DT Network (2011) (189)
Efficient Ranking from Pairwise Comparisons (2013) (187)
Variational methods for the Dirichlet process (2004) (186)
Hierarchies of Adaptive Experts (1991) (186)
Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning (2018) (184)
The Handbook of Brain Theory and Neural Networks (2002) (182)
Toward a protein profile of Escherichia coli: Comparison to its transcription profile (2003) (182)
Knowing when you're wrong: building fast and reliable approximate query processing systems (2014) (181)
Series foreword (2003) (180)
Generalized Zero-Shot Learning with Deep Calibration Network (2018) (179)
Trading relations between tongue-body raising and lip rounding in production of the vowel /u/: a pilot "motor equivalence" study. (1993) (179)
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (2019) (178)
Near-Optimal Algorithms for Minimax Optimization (2020) (177)
Understanding the acceleration phenomenon via high-resolution differential equations (2018) (174)
Semi-supervised Learning via Gaussian Processes (2004) (171)
A Berkeley View of Systems Challenges for AI (2017) (171)
Statistical debugging: simultaneous identification of multiple bugs (2006) (170)
A Competitive Modular Connectionist Architecture (1990) (167)
Tree-Structured Stick Breaking for Hierarchical Data (2010) (167)
Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones (1999) (167)
Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning (2014) (166)
Generic constraints on underspecified target trajectories (1989) (165)
Genome-Wide Requirements for Resistance to Functionally Distinct DNA-Damaging Agents (2005) (164)
Learning from Dyadic Data (1998) (163)
Neighbor-Dependent Ramachandran Probability Distributions of Amino Acids Developed from a Hierarchical Dirichlet Process Model (2010) (163)
Thin Junction Trees (2001) (162)
Artificial Intelligence—The Revolution Hasn’t Happened Yet (2019) (161)
SparkNet: Training Deep Networks in Spark (2015) (161)
Adding vs. Averaging in Distributed Primal-Dual Optimization (2015) (160)
First-order Methods Almost Always Avoid Saddle Points (2017) (157)
Sharing Features among Dynamical Systems with Beta Processes (2009) (157)
The SCADS Director: Scaling a Distributed Storage System Under Stringent Performance Requirements (2011) (154)
Computational models of sensorimotor integration (1997) (153)
Matrix concentration inequalities via the method of exchangeable pairs (2012) (153)
Distributed optimization with arbitrary local solvers (2015) (152)
Online System Problem Detection by Mining Patterns of Console Logs (2009) (149)
L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data (2018) (149)
Communication-Efficient Online Detection of Network-Wide Anomalies (2007) (144)
Automating model search for large scale machine learning (2015) (144)
Why the logistic function? A tutorial discussion on probabilities and neural networks (1995) (144)
An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators (2008) (139)
An Analysis of the Convergence of Graph Laplacians (2010) (139)
Multiple Non-Redundant Spectral Clustering Views (2010) (138)
Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding (2008) (138)
Modeling Events with Cascades of Poisson Processes (2010) (136)
Stochastic Cubic Regularization for Fast Nonconvex Optimization (2017) (136)
The Big Data Bootstrap (2012) (136)
Nonparametric empirical Bayes for the Dirichlet process mixture model (2006) (136)
Learning to Control an Unstable System with Forward Modeling (1989) (136)
Nonparametric Link Prediction in Dynamic Networks (2012) (136)
Transferable Normalization: Towards Improving Transferability of Deep Neural Networks (2019) (135)
ON surrogate loss functions and f-divergences (2005) (134)
Obstacle Avoidance and a Perturbation Sensitivity Model for Motor Planning (1997) (134)
Sharp Convergence Rates for Langevin Dynamics in the Nonconvex Setting (2018) (133)
Unsupervised Learning from Dyadic Data (1998) (132)
Bayesian Bias Mitigation for Crowdsourcing (2011) (131)
Computational Consequences of a Bias toward Short Connections (1992) (130)
Mixtures of Probabilistic Principal Component Analyzers (2001) (128)
Structured Prediction, Dual Extragradient and Bregman Projections (2006) (127)
Beyond Independent Components: Trees and Clusters (2003) (126)
Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation (2013) (126)
First-order methods almost always avoid strict saddle points (2019) (126)
Learning from measurements in exponential families (2009) (126)
A Minimal Intervention Principle for Coordinated Movement (2002) (125)
Local Privacy and Statistical Minimax Rates (2013) (125)
Computer Intrusion Detection and Network Monitoring: A Statistical Viewpoint (2001) (123)
Variational methods for inference and estimation in graphical models (1997) (122)
Learning graphical models for stationary time series (2004) (121)
Minimax Probability Machine (2001) (120)
On the Computational Complexity of High-Dimensional Bayesian Variable Selection (2015) (120)
Computing regularization paths for learning multiple kernels (2004) (118)
Increased VO2 max with right-shifted Hb-O2 dissociation curve at a constant O2 delivery in dog muscle in situ. (1998) (118)
Blind One-microphone Speech Separation: A Spectral Learning Approach (2004) (118)
Learning Programs: A Hierarchical Bayesian Approach (2010) (117)
On Finding Local Nash Equilibria (and Only Local Nash Equilibria) in Zero-Sum Games (2019) (116)
Support vector machines for analog circuit performance representation (2003) (115)
The Role of Inertial Sensitivity in Motor Planning (1998) (115)
On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms (2019) (115)
Lower bounds on the performance of polynomial-time algorithms for sparse linear regression (2014) (114)
Mining Console Logs for Large-Scale System Problem Detection (2008) (114)
Provable Meta-Learning of Linear Representations (2020) (114)
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences (2016) (113)
Computational aspects of motor control and motor learning (2008) (113)
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox (2014) (112)
On the Theory of Transfer Learning: The Importance of Task Diversity (2020) (111)
Sampling can be faster than optimization (2018) (110)
Viewing the hand prior to movement improves accuracy of pointing performed toward the unseen contralateral hand (1997) (108)
Hidden Markov Decision Trees (1996) (108)
Regression on manifolds using kernel dimension reduction (2007) (108)
Shaping and policy search in reinforcement learning (2003) (106)
Perceptual distortion contributes to the curvature of human reaching movements (1994) (104)
On Nonconvex Optimization for Machine Learning: Gradients, Stochasticity, and Saddle Points (2019) (104)
On statistics, computation and scalability (2013) (102)
Consistent probabilistic outputs for protein function prediction (2008) (100)
Estimation, Optimization, and Parallelism when Data is Sparse (2013) (100)
Uncertainty Sets for Image Classifiers using Conformal Prediction (2020) (100)
Bayesian Haplotype Inference via the Dirichlet Process (2007) (99)
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization (2007) (99)
Approximating Posterior Distributions in Belief Networks Using Mixtures (1997) (98)
Asymptotic Convergence Rate of the EM Algorithm for Gaussian Mixtures (2000) (98)
Sulfur and Nitrogen Limitation in Escherichia coli K-12: Specific Homeostatic Responses (2005) (98)
Log-determinant relaxation for approximate inference in discrete Markov random fields (2006) (97)
Word Alignment via Quadratic Assignment (2006) (97)
On the Consistency of Ranking Algorithms (2010) (96)
Bayesian Nonparametric Latent Feature Models (2011) (96)
Dried blood spots for HIV-1 drug resistance and viral load testing: A review of current knowledge and WHO efforts for global HIV drug resistance surveillance. (2010) (94)
Robust Novelty Detection with Single-Class MPM (2002) (93)
Graphical models: Probabilistic inference (2002) (93)
Spectral Clustering with Perturbed Data (2008) (92)
Nonparametric decentralized detection using kernel methods (2005) (92)
MAD-Bayes: MAP-based Asymptotic Derivations from Bayes (2012) (92)
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes (2007) (91)
Boltzmann Chains and Hidden Markov Models (1994) (91)
Combining Visualization and Statistical Analysis to Improve Operator Confidence and Efficiency for Failure Detection and Localization (2005) (91)
Information Constraints on Auto-Encoding Variational Bayes (2018) (91)
Ergodic mirror descent (2011) (90)
L1-regularized Neural Networks are Improperly Learnable in Polynomial Time (2015) (90)
JOINT MODELING OF MULTIPLE TIME SERIES VIA THE BETA PROCESS WITH APPLICATION TO MOTION CAPTURE SEGMENTATION (2013) (88)
Probabilistic Harmonization and Annotation of Single-cell Transcriptomics Data with Deep Generative Models (2019) (87)
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation (2019) (86)
Leo Breiman (2011) (86)
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo (2018) (86)
A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm (2019) (86)
A Python library for probabilistic analysis of single-cell omics data (2022) (86)
Local linear perceptrons for classification (1996) (85)
Bayesian Nonparametric Methods for Learning Markov Switching Processes (2010) (83)
A Dynamical Systems Perspective on Nesterov Acceleration (2019) (83)
The Sticky HDP-HMM: Bayesian Nonparametric Hidden Markov Models with Persistent States (2009) (83)
Less than a Single Pass: Stochastically Controlled Stochastic Gradient (2016) (83)
Phylogenetic Inference via Sequential Monte Carlo (2012) (83)
Acceleration via Symplectic Discretization of High-Resolution Differential Equations (2019) (83)
Beta Processes, Stick-Breaking and Power Laws (2011) (82)
Probabilistic models of text and images (2004) (82)
How Does Learning Rate Decay Help Modern Neural Networks (2019) (81)
Variational Learning for Switching State-Space Models (2001) (81)
On Symplectic Optimization (2018) (79)
Computing upper and lower bounds on likelihoods in intractable networks (1996) (79)
Efficient Stepwise Selection in Decomposable Models (2001) (79)
Distribution-Free, Risk-Controlling Prediction Sets (2021) (77)
Statistical Debugging of Sampled Programs (2003) (77)
An introduction to linear algebra in parallel distributed processing (1986) (77)
Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data (2018) (77)
Union support recovery in high-dimensional multivariate regression (2008) (76)
Minmax Optimization: Stable Limit Points of Gradient Descent Ascent are Locally Optimal (2019) (76)
Robust Optimization for Fairness with Noisy Protected Groups (2020) (76)
A more biologically plausible learning rule than backpropagation applied to a network model of cortical area 7a. (1991) (75)
A latent variable model for chemogenomic profiling (2005) (75)
A unified treatment of multiple testing with prior knowledge using the p-filter (2017) (75)
Improving the Mean Field Approximation Via the Use of Mixture Distributions (1999) (75)
Effect of NO, vasodilator prostaglandins, and adenosine on skeletal muscle angiogenic growth factor gene expression. (1999) (75)
Robust design of biological experiments (2005) (75)
Averaging Stochastic Gradient Descent on Riemannian Manifolds (2018) (74)
Goal-based speech motor control: A theoretical framework and some preliminary data (1995) (74)
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization (2020) (74)
The Organization of Action Sequences: Evidence From a Relearning Task. (1995) (73)
50 Strategies for Teaching English Language Learners (2015) (73)
Regularized Discriminant Analysis, Ridge Regression and Beyond (2010) (73)
Covariances, Robustness, and Variational Bayes (2017) (73)
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes (2015) (72)
A Swiss Army Infinitesimal Jackknife (2018) (72)
Local Privacy, Data Processing Inequalities, and Statistical Minimax Rates (2013) (72)
Learning Graphical Models with Mercer Kernels (2002) (71)
Active site prediction using evolutionary and structural information (2010) (71)
Parallel Correlation Clustering on Big Graphs (2015) (71)
Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models (2012) (70)
Is There an Analog of Nesterov Acceleration for MCMC? (2019) (69)
Combinatorial Clustering and the Beta Negative Binomial Process (2011) (69)
Kernel Feature Selection via Conditional Covariance Minimization (2017) (67)
A Model of the Learning of Arm Trajectories from Spatial Deviations (1994) (67)
Feature allocations, probability functions, and paintboxes (2013) (66)
Structured Prediction via the Extragradient Method (2005) (65)
Bayesian Nonnegative Matrix Factorization with Stochastic Variational Inference (2014) (63)
Logos: a Modular Bayesian Model for de Novo Motif Detection (2004) (63)
Simultaneous classification and relevant feature identification in high-dimensional spaces: application to molecular profiling data (2003) (62)
Constrained supervised learning (1992) (62)
Mixed Membership Matrix Factorization (2010) (62)
Cyclades: Conflict-free Asynchronous Machine Learning (2016) (61)
Active Learning for Nonlinear System Identification with Guarantees (2020) (61)
Modular and hierarchical learning systems (1998) (60)
Angiogenic growth factor mRNA responses to passive and contraction-induced hyperperfusion in skeletal muscle. (1998) (60)
Stochastic Gradient Descent Escapes Saddle Points Efficiently (2019) (60)
Ancestor Sampling for Particle Gibbs (2012) (59)
Genome-scale phylogenetic function annotation of large and diverse protein families. (2011) (59)
Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates (2003) (58)
A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements (2019) (58)
Optimality guarantees for distributed statistical estimation (2014) (58)
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm (2019) (58)
Learning in Boltzmann Trees (1994) (58)
Extensions of the Informative Vector Machine (2004) (57)
Bayesian inference for queueing networks and modeling of internet services (2010) (57)
Bayesian semiparametric Wiener system identification (2013) (57)
ML-LOO: Detecting Adversarial Examples with Feature Attribution (2019) (57)
Regression with input-dependent noise: A Gaussian process treatment (1998) (57)
Iterative Discovery of Multiple AlternativeClustering Views (2014) (55)
Real-Time Machine Learning: The Missing Pieces (2017) (55)
The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features (2008) (55)
A Lyapunov Analysis of Accelerated Methods in Optimization (2021) (55)
A randomization test for controlling population stratification in whole-genome association studies. (2007) (54)
Multiple-sequence functional annotation and the generalized hidden Markov phylogeny (2004) (54)
EP-GIG Priors and Applications in Bayesian Sparse Learning (2012) (54)
Nonparametric Bayesian Co-clustering Ensembles (2011) (54)
Online control of the false discovery rate with decaying memory (2017) (53)
SMaSH: a benchmarking toolkit for human genome variant calling (2013) (53)
Active spectral clustering via iterative uncertainty reduction (2012) (52)
Cluster Forests (2011) (52)
Distributed matrix completion and robust factorization (2011) (52)
scvi-tools: a library for deep probabilistic analysis of single-cell omics data (2021) (52)
Experience Mining Google's Production Console Logs (2010) (52)
Age-related changes in serum insulin-like growth factor-I, insulin-like growth factor-I binding protein-3 and articular cartilage structure in Thoroughbred horses. (2010) (51)
Hierarchical Models , Nested Models and Completely Random Measures (2010) (51)
Automatic exploration of datacenter performance regimes (2009) (51)
Probabilistic harmonization and annotation of single‐cell transcriptomics data with deep generative models (2021) (51)
Dimensionality Reduction for Spectral Clustering (2011) (51)
A statistical approach to decision tree modeling (1994) (50)
Estimating Dependency Structure as a Hidden Variable (1997) (50)
Stick-Breaking Beta Processes and the Poisson Process (2012) (50)
Hierarchical Bayesian Models for Applications in Information Retrieval (2003) (50)
Variational Consensus Monte Carlo (2015) (50)
Robust Sparse Hyperplane Classifiers: Application to Uncertain Molecular Profiling Data (2004) (50)
Competing Bandits in Matching Markets (2019) (48)
Active Learning for Crowd-Sourced Databases (2012) (48)
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Key Design Issues for Large Low Profile Container Cranes (2019) (0)
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Probabilistic Models of Evolution and Language Change (2010) (0)
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Çò ××ññññ¬òòøø Ööððüüøøóò Óö Òóöññððþþþ ¹¹ùø Òò Óòòòòøøóò× Øó ×ôøööð Ðù×øøööòò (2005) (0)
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Approximate Sherali-Adams Relaxations for MAP Inference via Entropy Regularization (2019) (0)
Effect of the Electrical Stimulation Site on Architectural Changes in Tibialis Anterior (2019) (0)
Unsupervised Kernel Dimension Reduction Supplemental Material (2010) (0)
Inactivation of SARS-CoV-2 on Surfaces by Cold-Plasma-Generated Reactive Species (2023) (0)
8th Workshop on Bayesian Nonparametrics (2011) (0)
Saturating Splines and Feature Selection Nicholas Boyd Trevor Hastie Stephen Boyd Benjamin Recht (2017) (0)
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New Honor, New Initiatives, and New Impact to Come (2011) (0)
Hierarchical Dirichlet Processes Author ( s ) : (2011) (0)
Probabilistic Multilevel Clustering via Composite Transportation Distance : Supplementary Material (2019) (0)
A Dual Receptor Cross-talk Model of G protein-coupled Signal Transduction Running Head : Dual Receptor GPCR Crosstalk Model (2008) (0)
Incorporating an Increase in Plant-Based Food Choices into a model of Culturally Responsive Care for Obesity in Hispanic/Latino Adults and Children (2019) (0)
Idiopathic horner syndrome diagnosed remotely using telemedicine (2021) (0)
An immuno-protective treatment strategy for autoimmune diseases (P5201) (2013) (0)
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Structural Imsets: Fundamentals (2005) (0)
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The Variable Genomic NK Cell Receptor Locus Is a Key Determinant of CD4+ T Cell Responses During Viral Infection (2020) (0)
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Heavy-Tailed Processes for Selective Shrinkage (2010) (0)
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Information Divergence Measures and Surrogate Loss Functions (2006) (0)
RobULA: Efficient Sampling for Robust Bayesian Inference (2019) (0)
A System for Offline Cursive Handwritten Word Recognition (2008) (0)
Joint probabilistic detection , association , & localization I : Hierarchical modeling (2009) (0)
IEEE International Conference on Image Processing (ICIP 2007). Volume 3, Sept. 16 2007 - Oct. 19 2007 (2007) (0)
Real-time continuous FTIR monitoring of Stromboli Volcano (2009) (0)
Fast Measurements of Robustness to Changing Priors in Variational Bayes (2016) (0)
The 5th Artificial Intelligence of Things (AIoT) Workshop (2022) (0)
On the effect of analog noise in discrete-time analog computations (2007) (0)
Impact of Signal Processing and of Our Work (2010) (0)
Proceedings of the 10th International Conference on Neural Information Processing Systems (1997) (0)
Advances in neural information processing systems: Proceedings of the first 12 conferences (CDROM) (2001) (0)
The Problem of Representative Choice (2005) (0)
The 4th Artificial Intelligence of Things (AIoT) Workshop (2021) (0)
Intravenous Infusion of Liposomal Clodronate Blocks Clearance of Opsonized Erythrocytes in Dogs. (2004) (0)
Automated music analysis using dynamic graphical models (2005) (0)
Prediction-Powered Inference (2023) (0)
Robust Estimation for Non-parametric Families via Generative Adversarial Networks (2022) (0)
Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty (2020) (0)
A Primal-dual Approach for Solving Variational Inequalities with General-form Constraints (2022) (0)
DS 102 Data, Inference, and Optional Material: Online False Discovery Rate Control (2020) (0)
Beta processes , stick-breaking , and power laws MS Project Report (2011) (0)
Applied Nonparametric Bayes (2009) (0)
Continuous-time Analysis for Variational Inequalities: An Overview and Desiderata (2022) (0)
Empirical Gateaux Derivatives for Causal Inference (2022) (0)
A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning (2023) (0)
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback (2022) (0)
Advances in Neural Information Processing Systems 1, [NIPS Conference, Denver, Colorado, USA, 1988] (1989) (0)
Parallelizing Contextual Bandits (2021) (0)
Online Learning in Stackelberg Games with an Omniscient Follower (2023) (0)
Accelerated First-Order Optimization under Nonlinear Constraints (2023) (0)
Learning Two-Player Markov Games: Neural Function Approximation and Correlated Equilibrium (2022) (0)
Revisiting the ACVI Method for Constrained Variational Inequalities (2022) (0)
Valid Inference after Causal Discovery (2022) (0)
Deterministic Nonsmooth Nonconvex Optimization (2023) (0)
Representation Learning as Finding Necessary and Sufﬁcient Causes (2022) (0)
Perturbed Iterate Analysis for Asynchronous Stochastic Optimization Horia Mania Research Project (2019) (0)
The Impact of Cultural Embeddedness on the Implementation of an Artificial Intelligence Program at Triage: A Qualitative Study (2022) (0)
Advancing EBP culture and competencies through an academic-research partnership: Process and outcomes of an EBP scholar program. (2022) (0)
Corrigendum: Plant-Based Diets Are Associated With Lower Adiposity Levels Among Hispanic/Latino Adults in the Adventist Multi-Ethnic Nutrition (AMEN) Study (2019) (0)
musclecontraction-induced hyperperfusion in skeletal Angiogenic growth factor mRNA responses to passive (2015) (0)
muscle in situ delivery in dog 2 dissociation curve at a constant O (2015) (0)
Multivariate Nonlinear Regression with Semiparametric Latent Factor Models (2005) (0)

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