Alexander J. Smola

Alexander J. Smola's AcademicInfluence.com Rankings

Alexander J. Smola

Computer Science

#1989

World Rank

#2067

Historical Rank

Machine Learning

#94

World Rank

#94

Historical Rank

Database

#158

World Rank

#163

Historical Rank

computer-science Degrees

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Computer Science

Alexander J. Smola's Degrees

PhD Computer Science University of Technology Sydney
Masters Computer Science University of Technology Sydney
Bachelors Computer Science University of Technology Sydney

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Alexander J. Smola'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

A tutorial on support vector regression (2004) (10276)
Nonlinear Component Analysis as a Kernel Eigenvalue Problem (1998) (8278)
Learning with kernels (1998) (6780)
Advances in kernel methods: support vector learning (1999) (5368)
Estimating the Support of a High-Dimensional Distribution (2001) (5079)
Support Vector Regression Machines (1996) (4145)
Hierarchical Attention Networks for Document Classification (2016) (3798)
A Kernel Two-Sample Test (2012) (3479)
Learning with Kernels: support vector machines, regularization, optimization, and beyond (2001) (3425)
Support Vector Method for Function Approximation, Regression Estimation and Signal Processing (1996) (2813)
New Support Vector Algorithms (2000) (2761)
Kernel Principal Component Analysis (1997) (2323)
Support Vector Method for Novelty Detection (1999) (1861)
A Kernel Method for the Two-Sample-Problem (2006) (1785)
Stacked Attention Networks for Image Question Answering (2015) (1657)
A Generalized Representer Theorem (2001) (1648)
Scaling Distributed Machine Learning with the Parameter Server (2014) (1586)
Correcting Sample Selection Bias by Unlabeled Data (2006) (1551)
Kernel methods in machine learning (2007) (1434)
Deep Sets (2017) (1434)
Measuring Statistical Dependence with Hilbert-Schmidt Norms (2005) (1392)
Input space versus feature space in kernel-based methods (1999) (1265)
Parallelized Stochastic Gradient Descent (2010) (1256)
Integrating structured biological data by Kernel Maximum Mean Discrepancy (2006) (1132)
Online learning with kernels (2001) (1097)
Advances in Large Margin Classifiers (2000) (1069)
Kernel PCA and De-Noising in Feature Spaces (1998) (1062)
Predicting Time Series with Support Vector Machines (1997) (1023)
Feature hashing for large scale multitask learning (2009) (946)
Kernels and Regularization on Graphs (2003) (906)
Protein function prediction via graph kernels (2005) (890)
A Hilbert Space Embedding for Distributions (2007) (834)
Sampling Matters in Deep Embedding Learning (2017) (748)
Sparse Greedy Matrix Approximation for Machine Learning (2000) (745)
A Kernel Statistical Test of Independence (2007) (715)
The connection between regularization operators and support vector kernels (1998) (690)
ResNeSt: Split-Attention Networks (2020) (680)
Efficient mini-batch training for stochastic optimization (2014) (644)
Recurrent Recommender Networks (2017) (582)
Distributed large-scale natural graph factorization (2013) (568)
Multi-Instance Kernels (2002) (545)
Covariate Shift by Kernel Mean Matching (2009) (524)
Stochastic Variance Reduction for Nonconvex Optimization (2016) (510)
Communication Efficient Distributed Machine Learning with the Parameter Server (2014) (503)
Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites (2000) (477)
Probabilities for SV Machines (2000) (451)
Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs (2019) (450)
An architecture for parallel topic models (2010) (448)
Learning Graph Matching (2007) (446)
Query Learning with Large Margin Classifiers (2000) (433)
COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking (2007) (424)
Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS) (2014) (421)
Like like alike: joint friendship and interest propagation in social networks (2011) (413)
Discovering geographical topics in the twitter stream (2012) (408)
Fastfood: Approximate Kernel Expansions in Loglinear Time (2013) (408)
Sparse Greedy Gaussian Process Regression (2000) (403)
Nonparametric Quantile Estimation (2006) (398)
Learning the Kernel with Hyperkernels (2005) (368)
Slow Learners are Fast (2009) (366)
Fast Kernels for String and Tree Matching (2002) (361)
Prior Knowledge in Support Vector Kernels (1997) (360)
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning (2017) (358)
Feature Selection via Dependence Maximization (2012) (347)
Kernel Methods for Measuring Independence (2005) (345)
On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion (1998) (333)
Supervised feature selection via dependence estimation (2007) (332)
Detecting and Correcting for Label Shift with Black Box Predictors (2018) (330)
Neural Information Processing Systems (1997) (326)
Hilbert space embeddings of conditional distributions with applications to dynamical systems (2009) (304)
Variational Reasoning for Question Answering with Knowledge Graph (2017) (300)
Kernel Methods for Missing Variables (2005) (284)
Bundle Methods for Regularized Risk Minimization (2010) (280)
Scalable inference in latent variable models (2012) (280)
Regression estimation with support vector learning machines (1996) (261)
Learning with non-positive kernels (2004) (259)
Compressed Video Action Recognition (2017) (248)
Deep Fried Convnets (2014) (246)
Hash Kernels for Structured Data (2009) (246)
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data (2006) (245)
Hilbert Space Embeddings of Hidden Markov Models (2010) (229)
Estimating labels from label proportions (2008) (224)
Dynamic Alignment Kernels (2000) (224)
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo (2015) (222)
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces (2003) (221)
Super-Samples from Kernel Herding (2010) (221)
The Need for Open Source Software in Machine Learning (2007) (219)
Invariant Feature Extraction and Classification in Kernel Spaces (1999) (218)
Shrinking the Tube: A New Support Vector Regression Algorithm (1998) (218)
Trend Filtering on Graphs (2014) (215)
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data (2020) (215)
Reducing the sampling complexity of topic models (2014) (210)
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy (2016) (207)
Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators (2001) (200)
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants (2015) (191)
A scalable modular convex solver for regularized risk minimization (2007) (191)
Parameter Server for Distributed Machine Learning (2013) (177)
Scalable distributed inference of dynamic user interests for behavioral targeting (2011) (177)
Heteroscedastic Gaussian process regression (2005) (176)
Support Vector Machine Reference Manual (1998) (173)
Randomized Nonlinear Component Analysis (2014) (168)
Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams (2015) (166)
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2016) (166)
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization (2016) (158)
Learning Networks of Heterogeneous Influence (2012) (158)
Fastfood - Computing Hilbert Space Expansions in loglinear time (2013) (155)
Collaborative competitive filtering: learning recommender using context of user choice (2011) (151)
Bundle Methods for Machine Learning (2007) (150)
Improving maximum margin matrix factorization (2008) (149)
Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes (2007) (147)
Human Action Segmentation and Recognition Using Discriminative Semi-Markov Models (2011) (144)
Neural Survival Recommender (2017) (141)
Experimentally optimal v in support vector regression for different noise models and parameter settings (2004) (139)
Unifying Divergence Minimization and Statistical Inference Via Convex Duality (2006) (138)
Predicting Structured Data (Neural Information Processing) (2007) (137)
Learning Steady-States of Iterative Algorithms over Graphs (2018) (133)
Kernel PCA pattern reconstruction via approximate pre-images. (1998) (132)
AIDE: Fast and Communication Efficient Distributed Optimization (2016) (132)
Discriminative human action segmentation and recognition using semi-Markov model (2008) (131)
Classification in a normalized feature space using support vector machines (2003) (128)
Regularized Principal Manifolds (1999) (125)
A Tutorial Introduction (2001) (125)
Asymptotically Optimal Choice of ε-Loss for Support Vector Machines (1998) (124)
A la Carte - Learning Fast Kernels (2014) (122)
Variance Reduction for Stochastic Gradient Optimization (2013) (122)
Stochastic Frank-Wolfe methods for nonconvex optimization (2016) (120)
Word Features for Latent Dirichlet Allocation (2010) (119)
Near-optimal Supervised Feature Selection among Frequent Subgraphs (2009) (119)
Regularization with Dot-Product Kernels (2000) (117)
A dependence maximization view of clustering (2007) (117)
Friend or frenemy?: predicting signed ties in social networks (2012) (116)
Fast and Guaranteed Tensor Decomposition via Sketching (2015) (114)
Direct Optimization of Ranking Measures (2007) (113)
Hierarchical geographical modeling of user locations from social media posts (2013) (110)
Deep Factors for Forecasting (2019) (110)
Colored Maximum Variance Unfolding (2007) (109)
Convex Learning with Invariances (2007) (106)
General cost functions for support vector regression. (1998) (105)
Semiparametric Support Vector and Linear Programming Machines (1998) (104)
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations (2012) (104)
Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts (2013) (104)
Classification on proximity data with LP-machines (1999) (104)
Fast Differentially Private Matrix Factorization (2015) (102)
Linear programs for automatic accuracy control in regression. (1999) (102)
Kernelized Sorting (2008) (101)
From Regularization Operators to Support Vector Kernels (1997) (99)
An improved training algorithm for kernel Fisher discriminants (2001) (98)
Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces (1998) (95)
Kernel methods and the exponential family (2006) (95)
Variance Reduction in Stochastic Gradient Langevin Dynamics (2016) (89)
Unified analysis of streaming news (2011) (88)
A Second Order Cone programming Formulation for Classifying Missing Data (2004) (85)
A Short Introduction to Learning with Kernels (2002) (82)
Taxonomy discovery for personalized recommendation (2014) (81)
A Generic Approach for Escaping Saddle points (2017) (81)
Hash Kernels (2009) (80)
Gaussian process classification for segmenting and annotating sequences (2004) (80)
Language Models with Transformers (2019) (79)
Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text (2011) (78)
Elastic Machine Learning Algorithms in Amazon SageMaker (2020) (78)
Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods (2015) (77)
An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph (2020) (76)
Relative Novelty Detection (2009) (73)
Tighter Bounds for Structured Estimation (2008) (72)
Generalization Bounds and Consistency for Structured Labeling (2007) (70)
Sparse Kernel Feature Analysis (2002) (70)
Collaborative Email-Spam Filtering with the Hashing-Trick (2009) (69)
Nonparametric Quantile Regression (2005) (67)
Meta-Q-Learning (2019) (67)
Fast incremental method for smooth nonconvex optimization (2016) (64)
Hyperkernels (2002) (64)
Minimal Kernel Classifiers (2003) (62)
Kernel Constrained Covariance for Dependence Measurement (2005) (61)
Gene selection via the BAHSIC family of algorithms (2007) (61)
Tailoring density estimation via reproducing kernel moment matching (2008) (60)
CoBaFi: collaborative bayesian filtering (2014) (60)
Exponential Families for Conditional Random Fields (2004) (58)
Doubly Robust Covariate Shift Correction (2015) (57)
Gaussian Processes and SVM: Mean Field and Leave-One-Out (2000) (56)
The kernel mutual information (2003) (56)
Discriminative frequent subgraph mining with optimality guarantees (2010) (56)
Learning via Hilbert Space Embedding of Distributions (2007) (55)
Laplace Propagation (2003) (55)
DiFacto: Distributed Factorization Machines (2016) (55)
Who Supported Obama in 2012?: Ecological Inference through Distribution Regression (2015) (54)
Introduction to support vector learning (1999) (51)
Fast Stochastic Methods for Nonsmooth Nonconvex Optimization (2016) (51)
Neural Machine Translation with Recurrent Attention Modeling (2016) (51)
Inferring Movement Trajectories from GPS Snippets (2015) (48)
Multitask Learning without Label Correspondences (2010) (47)
Collaborative Filtering on a Budget (2010) (47)
Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data (2017) (47)
Regularization Networks and Support Vector Machines (2000) (45)
ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly (2014) (44)
Improving Semantic Segmentation via Self-Training (2020) (43)
Distribution Matching for Transduction (2009) (43)
Fast Incremental Method for Nonconvex Optimization (2016) (43)
IntervalRank: isotonic regression with listwise and pairwise constraints (2010) (43)
A Kernel Approach to Comparing Distributions (2007) (42)
Adapting Codes and Embeddings for Polychotomies (2002) (42)
Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling (2013) (41)
Fair and balanced: learning to present news stories (2012) (40)
Introduction to Machine Learning (2020) (40)
Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising (2014) (40)
The Falling Factorial Basis and Its Statistical Applications (2014) (39)
Simpler knowledge-based support vector machines (2006) (39)
Learning high-order MRF priors of color images (2006) (38)
Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference (2015) (38)
Kernel-Based Machine Learning Lab (2016) (38)
Step Size Adaptation in Reproducing Kernel Hilbert Space (2006) (37)
Wearable sensor activity analysis using semi-Markov models with a grammar (2010) (37)
Bounds on Error Expectation for SVM (2000) (37)
State Space LSTM Models with Particle MCMC Inference (2017) (36)
Linear Discriminant and Support Vector Classifiers (2000) (35)
Multiple domain user personalization (2011) (35)
Entropy Numbers, Operators and Support Vector Kernels (1999) (34)
Support Vector Machines and Kernel Algorithms (2002) (33)
Support Vector Machines and Kernel Algorithms (2002) (33)
Kernel Measures of Independence for non-iid Data (2008) (32)
Adaptive collaborative filtering (2008) (32)
AdaDelay: Delay Adaptive Distributed Stochastic Optimization (2016) (31)
Joint Training of Ratings and Reviews with Recurrent Recommender Networks (2016) (31)
P3O: Policy-on Policy-off Policy Optimization (2019) (31)
Concepts and Tools (2001) (30)
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation (2020) (30)
Communication Efficient Coresets for Empirical Loss Minimization (2015) (30)
GACV for Support Vector Machines (2000) (30)
A Review of Kernel Methods in Machine Learning (2006) (29)
AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization (2015) (29)
Deep Factors with Gaussian Processes for Forecasting (2018) (29)
Bioresorbable terpolymers based on L-lactide, glycolide and trimethylene carbonate with shape memory behaviour (2014) (29)
Scalable clustering of news search results (2011) (28)
Introduction to Large Margin Classifiers (2000) (26)
Binet-Cauchy Kernels (2004) (26)
Support Vector Machines (2005) (25)
Kernel Methods and Support Vector Machines (2003) (25)
Asymptotically optimal choice of varepsilon-loss for support vector machines. (1998) (24)
Machine learning using hyperkernels (2003) (24)
Annotating Needles in the Haystack without Looking: Product Information Extraction from Emails (2015) (24)
Robust Ensemble Learning for Data Mining (2000) (24)
Kernel method for percentile feature extraction (2000) (23)
Bayesian Kernel Methods (2002) (23)
Symbolic Music Generation with Transformer-GANs (2021) (23)
Fast hierarchical Gaussian processes (2015) (22)
Parallel Online Learning (2011) (22)
Adaptive Margin Support Vector Machines (2000) (22)
Linear-Time Estimators for Propensity Scores (2011) (22)
Bid generation for advanced match in sponsored search (2011) (21)
Linear support vector machines via dual cached loops (2012) (21)
MLSys: The New Frontier of Machine Learning Systems (2019) (21)
SysML: The New Frontier of Machine Learning Systems (2019) (20)
Computing the Bayes Kernel Classifier (2000) (20)
Efficient Multitask Feature and Relationship Learning (2017) (20)
Hokusai - Sketching Streams in Real Time (2012) (20)
Exponential Stochastic Cellular Automata for Massively Parallel Inference (2016) (20)
Entropy Numbers of Linear Function Classes (2000) (20)
Energy-Based Models (2007) (19)
Large-Scale Multiclass Transduction (2005) (19)
Using Navigation to Improve Recommendations in Real-Time (2016) (18)
TraDE: Transformers for Density Estimation (2020) (18)
Stochastic Frank-Wolfe methods for nonconvex optimization (2016) (18)
Kernel Machines and Boolean Functions (2001) (18)
Hilbert space embeddings in dynamical systems (2003) (18)
Explaining Reviews and Ratings with PACO: Poisson Additive Co-Clustering (2015) (17)
FastPoint: Scalable Deep Point Processes (2019) (17)
Support vector machine learning (2001) (17)
Convex Cost Functions for Support Vector Regression (1998) (17)
Machine Learning with Hyperkernels (2003) (17)
Spectral Methods for Indian Buffet Process Inference (2014) (16)
Guest editorial: model selection and optimization in machine learning (2011) (16)
Beyond the Margin (2000) (16)
A Tutorial Review of RKHS Methods in Machine Learning (2005) (15)
Advanced Lectures on Machine Learning (2003) (15)
An Adversarial View of Covariate Shift and A Minimax Approach (2009) (15)
Data Driven Resource Allocation for Distributed Learning (2015) (15)
Kernel extrapolation (2006) (15)
v-Arc: Ensemble Learning in the Presence of Outliers (1999) (15)
Preferential Attachment in Graphs with Affinities (2015) (14)
Large Margin Classification for Moving Targets (2002) (14)
Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning (2015) (14)
Semi-Markov Models for Sequence Segmentation (2007) (14)
A Short Tour of Kernel Methods for Graphs (2005) (14)
Boîte à outils SVM simple et rapide (2005) (13)
Invariances in Classification: an efficient SVM implementation (2005) (13)
Quantization Functionals and Regularized Principal Manifolds (1998) (13)
Newton-Like Methods for Nonparametric Independent Component Analysis (2006) (12)
Multimodal AutoML on Structured Tables with Text Fields (2021) (12)
Continuous Doubly Constrained Batch Reinforcement Learning (2021) (12)
Instant foodie: predicting expert ratings from grassroots (2013) (12)
Robust Near-Isometric Matching via Structured Learning of Graphical Models (2008) (11)
Kernel Fisher Discriminant (2001) (11)
Regret Bounds for Deterministic Gaussian Process Bandits (2012) (11)
Web-scale multi-task feature selection for behavioral targeting (2012) (11)
Une boîte à outils rapide et simple pour les SVM (2004) (10)
Experimentally optimal nu in support vector regression for different noise models and parameter settings (2005) (10)
Generalized Support Vector Machines (2000) (9)
FastEx: Hash Clustering with Exponential Families (2012) (9)
Natural Regularization from Generative Models (2000) (9)
A General Regression Framework for Learning String-to-String Mappings (2007) (9)
Optimal Web-Scale Tiering as a Flow Problem (2010) (9)
Parametric model-based clustering (2005) (8)
The Nested Chinese Restaurant Franchise Process: User Tracking and Document Modeling (2013) (8)
Lernen mit Kernen (1999) (8)
Go for a Walk and Arrive at the Answer: Reasoning Over Knowledge Bases with Reinforcement Learning (2017) (8)
Transductive Gaussian Process Regression with Automatic Model Selection (2006) (8)
Entropy Numbers for Convex Combinations and MLPs (2000) (8)
Deep Quantile Aggregation (2021) (7)
Large Margin Bank Boundaries for Ordinal Regression (2000) (7)
Efficient Algorithms for Max-Margin Structured Classification (2007) (7)
Generalization bounds and learning rates for Regularized principal manifolds (1998) (7)
Exponential Families and Kernels (2004) (7)
Recognizing Variables from Their Data via Deep Embeddings of Distributions (2019) (7)
Generalization Bounds for Convex Combinations of Kernel Functions (1998) (6)
Delayed Proximal Gradient Methods (2013) (6)
Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning (2008) (6)
Deep Explicit Duration Switching Models for Time Series (2021) (6)
Biodegradowalne polimery z pamięcią kształtu (2010) (6)
Elements of Statistical Learning Theory (2001) (6)
Advanced Lectures on Machine Learning: Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures (2003) (5)
Lernen mit Kernen Support-Vektor-Methoden zur Analyse hochdimensionaler Daten (1999) (5)
Optimal Message Scheduling for Aggregation (2018) (5)
Support Vectors and Statistical Mechanics (2000) (5)
Transformer on a Diet (2020) (5)
Spectral Methods for Nonparametric Models (2017) (4)
Improving Maximum Margin Matrix Margin Factorization (2008) (4)
Boron-chelate assisted synthesis of new bipyrazole derivatives (2018) (4)
A Compression Framework for Generating User Profiles (2010) (4)
Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data (2020) (4)
Distributed Flow Algorithms for Scalable Similarity Visualization (2010) (3)
Dive into Deep Learning (2021) (3)
A project of bioresorbable self-expanding vascular stents. The crimping process numerical simulation (2018) (3)
The Entropy Regularization Information Criterion (1999) (3)
Kernel peA and DeNoising in Feature Spaces (1998) (3)
Choosing /spl nu/ in support vector regression with different noise models-theory and experiments (2000) (3)
Combining near-optimal feature selection with gSpan (2008) (3)
Attributing Hacks (2016) (2)
Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network (2020) (2)
Badania mechanizmu biodegradacji in vivo terpolimerów z pamięcią kształtu (2011) (2)
McKernel: A Library for Approximate Kernel Expansions in Log-linear Time (2017) (2)
Kernel Feature Extraction (2001) (2)
Bayesian Kernel Models (2003) (2)
NICTA at TRECVID 2005 Shot Boundary Detection Task (2005) (2)
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning (2020) (2)
Bloom Origami Assays: Practical Group Testing (2020) (2)
COLLABORATIVE SPAM FILTERING WITH THE HASHING TRICK (2009) (2)
Natural Regularization in SVMs (2015) (1)
Cuckoo Linear Algebra (2015) (1)
Nowe semikrystaliczne bioresorbowalne materiały z pamięcią kształtu (2009) (1)
Canopy Fast Sampling with Cover Trees (2017) (1)
OPTIMIZED MAXIMUM MEAN DISCREPANCY (2016) (1)
Margin Distribution and Soft Margin (2000) (1)
Learning as Search Optimization (2007) (1)
Single-Class Problems: Quantile Estimation and Novelty Detection (2001) (1)
A kernel method to comparing distributions (2007) (1)
Joint Hacking and Latent Hazard Rate Estimation (2016) (1)
Correlates of homicide: new space/time interaction tests for spatiotemporal point processes (2013) (1)
Robust Ensemble Learning for Data (2000) (1)
Bound on the Leave-One-Out Error for Density Support Estimation using nu-SVMs (2001) (1)
Step size-adapted online support vector learning (2005) (1)
Spectral Methods for the Hierarchical Dirichlet Process (2015) (1)
Towards a Strategy for Boosting Regressors (2000) (1)
[Surgical prevention of acute stroke in atherosclerotic carotid stenosis]. (2015) (1)
Proc.17th Int Conference on Machine Learning (2000) (1)
A Machine Learning Approach to Technology Enhanced Learning (2010) (1)
F2F: A Library For Fast Kernel Expansions (2017) (1)
svlab - A Kernel Methods Package (2003) (1)
The BAHSIC family of gene selection algorithms (2006) (1)
Attributing hacks with survival trend filtering (2017) (1)
ACCAMS (2015) (1)
Measurement and modeling of eye-mouse behavior (2013) (1)
Joint Regularization (2005) (1)
MFSPFA: An Enhanced Filter based Feature Selection Algorithm (2020) (0)
Kangaroo Mother Care and Traditional Care (2019) (0)
Measuring Similarity with Kernels (2007) (0)
Scalable graph kernels with approximate matching of subtree patterns (2010) (0)
Learning Theory Revisited (2001) (0)
Otrzymywanie nowych, wysokoelastycznych i bioresorbowalnych kopolimerów węglanów alifatycznych (2013) (0)
Risk and Loss Functions (2001) (0)
Degradacja hydrolityczna rusztowań komórkowych formowanych z terpolimerów; L-laktydu, glikolidu i TMC, oraz L-laktydu, glikolidu i ε-kaprolaktonu (2015) (0)
Sample based generalisation bounds (2004) (0)
Maximal Margin Perception (2000) (0)
Pre-Images and Reduced Set Methods (2001) (0)
Appendix to Supervised Feature Selection via Dependence Estimation (2006) (0)
Email-Spam Filtering with the Hashing-Trick (2009) (0)
Gaussian Process Belief Propagation (2007) (0)
非凸最適化のための確率的Frank‐Wolfe法【Powered by NICT】 (2016) (0)
Supplementary Material : Compressed Video Action Recognition (2018) (0)
1 Covariate Shift by Kernel Mean Matching (2008) (0)
Ëñóðð¸öøððøø¸ë Óððóôô¸òò Ë Blockinùùöññò×× Úò Blockin Blockin× Ò Ääööö Ååöööò Ðð×××¬¬ö× ½½½½»½½»¼¿ ½½½¿¿ (1999) (0)
Sparse GreedyGaussian Pro ess Regression (2001) (0)
Appendix : Kernelized Sorting (2008) (0)
Ocena wpływu simwastatyny na degradację terpolimeru z pamięcią kształtu (2012) (0)
Kernel Ma hines and Boolean Fun tions (2002) (0)
Sparse GreedyGaussian Pro ess Regression (2001) (0)
Machine Learning Program , National ICT for Australia , Canberra , ACT 0200 , Australia (2003) (0)
Notation and Symbols (2001) (0)
Tiering as a Stochastic Submodular Optimization Problem (2020) (0)
Supplementary Material for “ Trend Filtering on Graphs ” (2015) (0)
Universal Clustering with Regularization in Probabilistic Space (2005) (0)
Structured Prediction Based on Discriminative Models (2007) (0)
Discriminative Learning of Prediction Suffix Trees with the Perceptron Algorithm (2007) (0)
Leave-One-Out Methods (2000) (0)
A (stochastic) Em in General (2016) (0)
Graphical Models for the Internet (2011) (0)
Sample Based GeneralizationBounds 1 (1999) (0)
HashBox: Hash Hierarchical Segmentation exploiting Bounding Box Object Detection (2017) (0)
Dive into Deep Learning for Natural Language Processing (2019) (0)
Invariant Feature Extra tion andClassi ation in Kernel Spa (2000) (0)
Database Management Systems for Non-Volatile Memory (2015) (0)
Segmentation of Instances by Hashing (2017) (0)
RI:Small:Collaborative Research: Distributed Inference Algorithms for Machine Learning (2012) (0)
Deep Graphs (2018) (0)
United States Patent ( 10 ) Patent No . : US 8 , 160 , 668 B 2 Pav ( 45 ) Date of Patent : Apr . 17 , 2012 ( 54 ) PATHOLOGICAL CONDITION DETECTOR 3 (2017) (0)
Support-Vektor-Methoden zur Analyse hochdimensionaler Daten (1999) (0)
Kernel-based measures of dependence in the Macaque visual cortex (2005) (0)
Ëôôö×× Ööööý Ååøööü Ôôöóüüññøøóò Óö Åå Blockinòò Äääöòòòò (0)
Advances in Large Margin Classiiers Library of Congress Cataloging-in-publication Data Advances in Large Margin Classiiers / Edited Includes Bibliographical References and Index. Isbn 0-xxx-xxxxx-x (alk. Paper) 1. Machine Learning. 2. Algorithms. 3. Kernel Functions (1999) (0)
Advances in Large Margin Classiiers Library of Congress Cataloging-in-publication Data Advances in Large Margin Classiiers / Edited Includes Bibliographical References and Index. Isbn 0-xxx-xxxxx-x (alk. Paper) 1. Machine Learning. 2. Algorithms. 3. Kernel Functions (1999) (0)
Ëôôö×× Ööööý Ååøööü Ôôöóüüññøøóò Óö Åå Blockinòò Äääöòòòò (0)
Segmentation of Objects by Hashing (2017) (0)
Właściwości i parametry pamięci kształtu biodegradowalnych mieszanek otrzymanych z kopolimeru L-laktyd/glikolid i poli(bursztynianu butylenu) (2014) (0)
IRLI: Iterative Re-partitioning for Learning to Index (2021) (0)
Kernel-based dependence detection in the Macaque visual cortex (2005) (0)
Deep Q-Network with Proximal Iteration (2021) (0)
Kernel Algorithms Distribution Embeddings in Reproducing Kernel Hilbert Spaces (2009) (0)
Algorithms, Data, Hardware and Tools: A Perfect Storm (2018) (0)
Integrating User Feedback under Identity Uncertainty in Knowledge Base Construction (2019) (0)
Effect of depth of occurrence in contacts on characteristics of p-AlxGa1−xAs-p-GaAs-n-GaAs heterostructures (1991) (0)
Biodegradowalny polimerowy system uwalniania radiouczulaczabadania in vitro (2010) (0)
WWW 2011 invited tutorial overview: latent variable models on the internet (2011) (0)
Logic, Trees and Kernels (2003) (0)
KDD tutorial: The Dataminer Guide to Scalable Mixed-Membership and Nonparametric Bayesian Models (2013) (0)
[Anastomosis using the Valtrac ring--pro and con]. (2000) (0)
Regioned Episodic Reinforcement Learning (2021) (0)
Accepted for NIPS ’ 99 SV Estimation of a Distribution ’ s Support (1999) (0)
Improving Maximum Margin Matrix Factorization (best machine learning paper award) (2008) (0)
Kernel Conditional Graphical Models (2007) (0)
Structured Prediction Using Probabilistic Models (2007) (0)
The Entropy Regularisation Information Criterion (2000) (0)
The dataminer's guide to scalable mixed-membership and nonparametric bayesian models (2013) (0)
Zmiany struktury i wybranych właściwości terpolimerów z pamięcią kształtu wywołanych w procesie otrzymywania implantów metodą wtrysku oraz ich sterylizacji (2010) (0)
Modeling Structure via Graphical Models (2007) (0)
Kernel Extrapolations for Enzyme Classification (2004) (0)
Synthesis and properties of bioresorbable and highly flexible 1,3-trimethylene carbonate/ε-caprolactone copolymers (2012) (0)
Instance Hash Segmentation (2017) (0)

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