Venkatesh C. Saligrama

Venkatesh C. Saligrama's AcademicInfluence.com Rankings

Engineering

#6795

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#8138

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Electrical Engineering

#2066

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#2171

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Venkatesh C. Saligrama

Computer Science

#9013

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#9471

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Computational Linguistics

#2105

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#2127

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Machine Learning

#3840

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#3886

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Artificial Intelligence

#4166

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#4224

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Engineering
Computer Science

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Venkatesh C. Saligrama'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

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016) (2027)
Zero-Shot Learning via Semantic Similarity Embedding (2015) (559)
Zero-Shot Learning via Joint Latent Similarity Embedding (2015) (340)
Video anomaly detection based on local statistical aggregates (2012) (294)
Boolean Compressed Sensing and Noisy Group Testing (2009) (260)
Abnormal events detection based on spatio-temporal co-occurences (2009) (237)
Federated Learning Based on Dynamic Regularization (2021) (230)
Adaptive Neural Networks for Efficient Inference (2017) (220)
Information Theoretic Bounds for Compressed Sensing (2008) (168)
Distributed Detection in Sensor Networks With Packet Losses and Finite Capacity Links (2006) (151)
Foreground-Adaptive Background Subtraction (2009) (149)
Non-adaptive group testing: Explicit bounds and novel algorithms (2012) (137)
Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms (2011) (129)
Anomaly Detection with Score functions based on Nearest Neighbor Graphs (2009) (116)
Video Anomaly Identification (2010) (108)
Prediction of hospitalization due to heart diseases by supervised learning methods (2015) (107)
Wireless Ad Hoc Networks: Strategies and Scaling Laws for the Fixed SNR Regime (2006) (106)
Efficient Training of Very Deep Neural Networks for Supervised Hashing (2015) (103)
Supervised Sequential Classification Under Budget Constraints (2013) (98)
Graph-Constrained Group Testing (2010) (96)
Experimental realization of long-distance entanglement between spins in antiferromagnetic quantum spin chains (2015) (92)
Zero-Shot Recognition via Structured Prediction (2016) (92)
Zero Shot Detection (2018) (81)
Unique contributions of parvalbumin and cholinergic interneurons in organizing striatal networks during movement (2019) (76)
Pruning Random Forests for Prediction on a Budget (2016) (70)
Generalized Zero-Shot Recognition Based on Visually Semantic Embedding (2018) (69)
Abnormality detection using low-level co-occurring events (2011) (64)
Spectrum Enforcement and Liability Assignment in Cognitive Radio Systems (2008) (63)
Efficient Sensor Management Policies for Distributed Target Tracking in Multihop Sensor Networks (2008) (61)
Don’t Even Look Once: Synthesizing Features for Zero-Shot Detection (2019) (56)
Sparse signal processing with linear and non-linear observations: A unified shannon theoretic approach (2013) (55)
Feature-Budgeted Random Forest (2015) (54)
Stem surface roughness alters creep induced subsidence and 'taper-lock' in a cemented femoral hip prosthesis. (2001) (53)
Topic Discovery through Data Dependent and Random Projections (2013) (52)
Adaptive Classification for Prediction Under a Budget (2017) (52)
Crime and Punishment for Cognitive Radios (2008) (51)
A Novel Visual Word Co-occurrence Model for Person Re-identification (2014) (51)
Quantifying and Reducing Stereotypes in Word Embeddings (2016) (49)
Local Supervised Learning through Space Partitioning (2012) (47)
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction (2015) (47)
Distributed Tracking in Multihop Sensor Networks With Communication Delays (2007) (46)
Adaptive Neural Networks for Fast Test-Time Prediction (2017) (46)
Activity Based Matching in Distributed Camera Networks (2010) (45)
Modeling background activity for behavior subtraction (2008) (44)
Behavior Subtraction (2009) (43)
Motion segmentation and abnormal behavior detection via behavior clustering (2008) (42)
Multi-stage classifier design (2012) (40)
Group Membership Prediction (2015) (38)
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? (2019) (37)
An LP for Sequential Learning Under Budgets (2014) (36)
Sequential Optimization for Efficient High-Quality Object Proposal Generation (2015) (33)
Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena (2005) (32)
Deterministic Designs with Deterministic Guarantees: Toeplitz Compressed Sensing Matrices, Sequence Designs and System Identification (2008) (32)
Abnormal behavior detection and behavior matching for networked cameras (2008) (32)
Reliable Distributed Estimation with Intermittent Communications (2006) (32)
Model Selection by Linear Programming (2014) (31)
Local Anomaly Detection (2012) (30)
Thresholded Basis Pursuit: LP Algorithm for Order-Wise Optimal Support Recovery for Sparse and Approximately Sparse Signals From Noisy Random Measurements (2011) (29)
A new one-class SVM for anomaly detection (2013) (29)
Distributed Detection in Sensor Networks With Limited Range Multimodal Sensors (2007) (29)
Connected Sub-graph Detection (2014) (29)
Cheap Bandits (2015) (28)
Thresholded Basis Pursuit: Quantizing Linear Programming Solutions for Optimal Support Recovery and Approximation in Compressed Sensing (2008) (27)
PRISM: Person Reidentification via Structured Matching (2014) (26)
Modal Participation Analysis for Identifying Brake Squeal Mechanism (2000) (25)
Motion detection with an unstable camera (2008) (23)
BING++: A Fast High Quality Object Proposal Generator at 100fps (2015) (22)
Retrieval in Long-Surveillance Videos Using User-Described Motion and Object Attributes (2014) (22)
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers (2018) (22)
A Random-Walk Model for Distributed Computation in Energy-Limited Networks (2006) (22)
Debiasing Model Updates for Improving Personalized Federated Training (2021) (22)
On sensing capacity of sensor networks for the class of linear observation, fixed SNR models (2007) (22)
A Topic Modeling Approach to Ranking (2014) (21)
Detection and Localization in Sensor Networks Using Distributed FDR (2006) (21)
A technical framework for light- handed regulation of cognitive radios (2009) (21)
Learning Joint Feature Adaptation for Zero-Shot Recognition (2016) (20)
Efficient Distributed Topic Modeling with Provable Guarantees (2014) (19)
Efficient Minimax Signal Detection on Graphs (2014) (18)
Stochastic threshold group testing (2013) (17)
Axisymmetric finite element analysis of a debonded total hip stem with an unsupported distal tip. (1993) (17)
Robust Energy Efficient Cooperative Spectrum Sensing in Cognitive Radios (2007) (17)
Fast margin-based cost-sensitive classification (2014) (17)
On sensing capacity of sensor networks for a class of linear observation models (2007) (17)
Broadband Dispersion Extraction Using Simultaneous Sparse Penalization (2011) (16)
Remember the curse of dimensionality: the case of goodness-of-fit testing in arbitrary dimension (2016) (16)
Efficient Activity Retrieval through Semantic Graph Queries (2015) (16)
Distributed tracking in multi-hop networks with communication delays and packet losses (2005) (16)
Information theoretic bounds to sensing capacity of sensor networks under fixed SNR (2007) (16)
Minimax Optimal Sparse Signal Recovery With Poisson Statistics (2015) (15)
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency (2021) (15)
Noisy group testing: An information theoretic perspective (2009) (15)
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices (2019) (15)
Fundamental Limits on Sensing Capacity for Sensor Networks and Compressed Sensing (2008) (15)
A Mutual Information Characterization for Sparse Signal Processing (2011) (15)
Clustering and Community Detection With Imbalanced Clusters (2016) (14)
Necessary and Sufficient Conditions for Novel Word Detection in Separable Topic Models (2013) (14)
Structural similarity and distance in learning (2011) (14)
Comments on the Proof of Adaptive Stochastic Set Cover Based on Adaptive Submodularity and Its Implications for the Group Identification Problem in “Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations” (2017) (13)
Most large topic models are approximately separable (2015) (13)
One-Bit Distributed Sensing and Coding for Field Estimation in Sensor Networks (2007) (13)
Learning Mixed Membership Mallows Models from Pairwise Comparisons (2015) (13)
Classification in sensor networks (2004) (12)
Energy-Efficient Adaptive Classifier Design for Mobile Systems (2016) (12)
Learning Immune-Defectives Graph through Group Tests (2015) (12)
Video Anomaly Identification [ a Statistical Approach ] (12)
On Throughput Maximization and Interference Avoidance in Cognitive Radios (2008) (12)
Learning Efficient Anomaly Detectors from K-NN Graphs (2015) (12)
Connected Subgraph Detection with Mirror Descent on SDPs (2017) (12)
New statistic in P-value estimation for anomaly detection (2012) (11)
Fundamental Tradeoffs between Sparsity, Sensing Diversity and Sensing Capacity (2006) (11)
Spectral clustering with imbalanced data (2013) (11)
Unsupervised Sequential Sensor Acquisition (2017) (11)
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems (2016) (11)
Mild Blast Injury Produces Acute Changes in Basal Intracellular Calcium Levels and Activity Patterns in Mouse Hippocampal Neurons. (2018) (11)
Randomized Sequential Algorithms for Data Aggregation in Sensor Networks (2006) (11)
Probabilistic Semantic Retrieval for Surveillance Videos With Activity Graphs (2017) (11)
On Optimal Outage in Relay Channels With General Fading Distributions (2007) (11)
On compressed blind de-convolution of filtered sparse processes (2010) (11)
A new algorithm for outlier rejection in particle filters (2010) (10)
Efficient In-Network Processing Through Local Ad-Hoc Information Coalescence (2006) (10)
Cost aware Inference for IoT Devices (2019) (10)
Search and discovery in an uncertain networked world (2006) (10)
Information-theoretic bounds for adaptive sparse recovery (2014) (10)
Energy Efficient Policies for Distributed Target Tracking in Multihop Sensor Networks (2006) (10)
A multi-resolution approach for discovery and 3-D modeling of archaeological sites using satellite imagery and a UAV-borne camera (2016) (10)
Training Recurrent Neural Networks via Forward Propagation Through Time (2021) (10)
Memory Efficient Online Meta Learning (2021) (9)
Rapid: Rapidly accelerated proximal gradient algorithms for convex minimization (2014) (9)
Machine learning combining CT findings and clinical parameters improves prediction of length of stay and ICU admission in torso trauma (2021) (9)
Graph Resistance and Learning from Pairwise Comparisons (2019) (9)
Selective Classification via One-Sided Prediction (2020) (9)
Time Adaptive Recurrent Neural Network (2021) (8)
Distributed Detection in Sensor Networks with Limited Range Sensors (2007) (8)
Sparse signal recovery under Poisson statistics (2013) (8)
Dynamic Thresholding for Distributed Multiple Hypotheses Testing (2007) (8)
Resource Constrained Structured Prediction (2016) (8)
A Token-Based Approach for Distributed Computation in Sensor Networks (2011) (8)
Motion detection with false discovery rate control (2008) (8)
Learning to Approximate a Bregman Divergence (2020) (8)
Online Algorithm for Unsupervised Sensor Selection (2019) (8)
Near-Optimal Stochastic Threshold Group Testing (2013) (8)
Non-adaptive group testing with inhibitors (2014) (8)
Efficient detection and localization on graph structured data (2015) (7)
Learning Classifiers for Target Domain with Limited or No Labels (2019) (7)
Active Boosted Learning (ActBoost) (2011) (7)
Supervised Hashing with Deep Neural Networks (2015) (7)
Locally-Linear Learning Machines (L3M) (2013) (7)
Identification of uncertain systems described by linear fractional transformations (2003) (7)
Thresholded Basis Pursuit: Support Recovery for Sparse and Approximately Sparse Signals (2008) (7)
Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data (2021) (7)
A Provably Efficient Algorithm for Separable Topic Discovery (2015) (7)
Piecewise Linear Regression via a Difference of Convex Functions (2020) (7)
Algorithms and bounds for sensing capacity and compressed sensing with applications to learning graphical models (2008) (6)
A Topic Modeling Approach to Rank Aggregation (2014) (6)
Codes to unmask spectrum violators in cognitive radio systems (2008) (6)
Lower bounds for two-sample structural change detection in ising and Gaussian models (2017) (6)
An impossibility result for high dimensional supervised learning (2013) (6)
Exploratory search of long surveillance videos (2012) (6)
Classifying Unseen Instances by Learning Class-Independent Similarity Functions (2015) (6)
On the Macroscopic Effects of Local Interactions in Multi-hop Wireless Networks (2006) (6)
Correction to “Boolean Compressed Sensing and Noisy Group Testing” [Mar 12 1880-1901] (2015) (6)
How Transferable are Video Representations Based on Synthetic Data? (2022) (6)
Sample complexity of salient feature identification for sparse signal processing (2012) (5)
RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? (2019) (5)
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model (2020) (5)
Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data (2014) (5)
Effectively Leveraging Attributes for Visual Similarity (2021) (5)
Learning Bregman Divergences (2019) (5)
User-assisted reflection detection and feature point tracking (2013) (5)
A new geometric approach to latent topic modeling and discovery (2013) (5)
Information-Theoretic Characterization of Sparse Recovery (2014) (5)
Information theoretic bounds to performance of Compressed Sensing and Sensor Networks (2008) (5)
Efficient algorithms for linear polyhedral bandits (2016) (5)
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models (2019) (5)
Shallow RNNs: A Method for Accurate Time-series Classification on Tiny Devices (2019) (5)
Dynamic Model Selection for Prediction Under a Budget (2017) (5)
Person Re-identification via Structured Prediction (2014) (5)
Real-Time Activity Search of Surveillance Video (2012) (5)
Unsupervised camera network structure estimation based on activity (2009) (5)
Spectral Clustering with Unbalanced Data (2013) (4)
Dynamic inverse optimization (2001) (4)
Thresholded Basis Pursuit: An LP Algorithm for Achieving Optimal Support Recovery for Sparse and Approximately Sparse Signals from Noisy Random Measurements (2008) (4)
Reliable Tracking With Intermittent Communications (2006) (4)
Budget Learning via Bracketing (2020) (4)
Aperiodic Sequences With Uniformly Decaying Correlations With Applications to Compressed Sensing and System Identification (2012) (4)
Learning shared rankings from mixtures of noisy pairwise comparisons (2015) (4)
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability (2019) (4)
Outlier detection via localized p-value estimation (2009) (4)
Robust Distributed Detection with Limited Range Sensors (2007) (4)
Networked sensing information and control (2008) (4)
Revision of marginal probability assessments (2010) (3)
Bandit Quickest Changepoint Detection (2021) (3)
Performance guarantees in sensor networks (2004) (3)
Crowdsourcing with Sparsely Interacting Workers (2017) (3)
Introduction to the issue on anomalous pattern discovery for spatial, temporal, networked, and high-dimensional signals (2013) (3)
Compressed sensing of autoregressive processes (2009) (3)
Sensing-aware kernel SVM (2013) (3)
Graph Construction for Learning with Unbalanced Data (2011) (3)
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk (2022) (3)
Cost effective algorithms for spectral bandits (2015) (3)
Dynamic topic discovery through sequential projections (2013) (3)
On Universal Distributed Estimation of Noisy Fields with One-bit Sensors (2007) (3)
Sensing-aware classification with high-dimensional data (2011) (3)
Sensing aware dimensionality reduction for nearest neighbor classification of high dimensional signals (2012) (3)
Multi-Stage Classier Design (2012) (3)
Sensing structure in learning-based binary classification of high-dimensional data (2011) (3)
Online Algorithm for Unsupervised Sequential Selection with Contextual Information (2020) (3)
Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds (2018) (3)
Testing Changes in Communities for the Stochastic Block Model (2018) (3)
Capacity scaling in wireless ad-hoc networks with P/sub e/ (2004) (3)
RNNs Evolving in Equilibrium: A Solution to the Vanishing and Exploding Gradients (2019) (2)
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations (2018) (2)
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm (2020) (2)
Low Dimensional Visual Attributes: An Interpretable Image Encoding (2020) (2)
Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget (2017) (2)
Changes in Cement Mantle Stresses Due to Viscoelasticity and Stem-Cement Interface Conditions (1995) (2)
Minimax Rank-1 Factorization (2019) (2)
Necessary and sufficient conditions for robust identification of uncertain LTI systems (2004) (2)
Two stage decision system (2012) (2)
Sparse signal recovery under poisson statistics for online marketing applications (2014) (2)
Compressed Blind De-convolution (2009) (2)
A combined approach to multi-label multi-task learning (2012) (2)
A gene filter for comparative analysis of single-cell RNA-sequencing trajectory datasets (2019) (2)
Distributed Target tracking and localization in multi-hop networks (2006) (2)
Guest Editorial Inference and Learning over Networks (2016) (2)
Sensing Capacity of Sensor Networks : Fundamental Tradeoffs of SNR , Sparsity and Sensing Diversity (2007) (2)
Structured Prediction with Test-time Budget Constraints (2016) (2)
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs (2016) (1)
Sequential Learning without Feedback (2016) (1)
Learning for New Visual Environments with Limited Labels (2019) (1)
Anomalous cluster detection (2014) (1)
Algorithms for Linear Bandits on Polyhedral Sets (2015) (1)
Multi-stage classifier design (2013) (1)
Cost Sensitive Sequential Classification (2012) (1)
A Rank-SVM Approach to Anomaly Detection (2014) (1)
Graph-based Learning with Unbalanced Clusters (2012) (1)
Faster Convex Lipschitz Regression via 2-block ADMM (2021) (1)
Comments on the proof of adaptive submodular function minimization (2017) (1)
Distributed Tracking with Multi-hop Networks (2005) (1)
Faster Algorithms for Learning Convex Functions (2021) (1)
Compressive sensing bounds through a unifying framework for sparse models (2013) (1)
Activity Retrieval in Large Surveillance Videos (2014) (1)
Online local linear classification (2013) (1)
Noisy filtered sparse processes: Reconstruction and compression (2010) (1)
ActiveHedge: Hedge meets Active Learning (2022) (1)
Field of Groves: An Energy-Efficient Random Forest (2017) (1)
In-Network Decision Making Via Local Message-Passing (2005) (1)
Minimax Rank-$1$ Matrix Factorization (2020) (1)
Robust Text Classifier on Test-Time Budgets (2018) (1)
Probabilistic Belief Revision with Structural Constraints (2010) (1)
Decentralized compressive sensing (2010) (1)
Sensing and reconstruction of sparse phenomena bounds and algorithms (2009) (1)
Optimally Pruning Decision Tree Ensembles With Feature Cost (2016) (1)
Learning Classifiers for Domain Adaptation, Zero and Few-Shot Recognition Based on Learning Latent Semantic Parts. (2019) (1)
FedHeN: Federated Learning in Heterogeneous Networks (2022) (0)
717 Computer-Assisted Diagnosis of Colonic Polyps by Probe-Based Confocal Laser Endomicroscopy (2010) (0)
Condensing CNNs with Partial Differential Equations (2022) (0)
Max-Cost Discrete Function Evaluation Problem under a Budget (2015) (0)
"active Boosted Learning" Active Boosted Learning (actboost) (2016) (0)
Markov group testing (2010) (0)
An Information-Theoretic Approach for Sparse Recovery with Linear and Nonlinear Observations (2016) (0)
SENSING-AWARE CLASSIFICATIONWITH HIGH-DIMENSIONAL DATA (2016) (0)
Distributed Field Estimation with One–bit Sensors (2008) (0)
Implicit Active-Contouring with MRF (2009) (0)
Supplementary Material : Model Selection by Linear Programming (2014) (0)
Effectively Leveraging Attributes for Visual Similarity (2021) (0)
Sensor Selection by Linear Programming (2015) (0)
Learning Compositional Representations for Effective Low-Shot Generalization (2022) (0)
CTH05-4: Effect of Geometry on the Diversity-Multiplexing Tradeoff in Relay Channels (2006) (0)
ROBUST DISTRIBUTEDDETECTIONWITH LIMITEDRANGE SENSORS (2007) (0)
Supplementary Material : A Proof of Theorem 1 and Corollary 1 (2020) (0)
A Doubly Optimistic Strategy for Safe Linear Bandits (2022) (0)
Role of sparsity in high dimensional signal detection and estimation (2011) (0)
( SPECIAL SECTION - DISTRIBUTED SIGNAL PROCESSING IN SENSOR NETWORKS ) (2006) (0)
Limits on Testing Structural Changes in Ising Models (2020) (0)
3-D Finite Element Analysis of the Stem-Cement Interface in a Femoral Hip Prothesis with a Viscoelastic Cement Mantle (1996) (0)
Fine-grained Few-shot Recognition by Deep Object Parsing (2022) (0)
Learning Where to Fixate on Foveated Images (2018) (0)
Modeling Patterns of Activity and Detecting Abnormal Events with Low-Level Co-occurrences (2011) (0)
Unique contributions of parvalbumin and cholinergic interneurons in organizing striatal networks during movement (2019) (0)
A Token Based Algorithm to Distributed Computation in Sensor Networks (2011) (0)
Effectively Leveraging Attributes for Visual Similarity Supplementary (2021) (0)
Doubly-Optimistic Play for Safe Linear Bandits (2022) (0)
" Active Boosted Learning " (2016) (0)
Causal Inference for Time Series: A Linear Systems Approach (2017) (0)
Recherche vidéo à grande échelle au moyen d'interrogations qui définissent des relations entre des objets (2015) (0)
Minimax Rate for Learning From Pairwise Comparisons (2019) (0)
Bayesian filtering without an observation model (2012) (0)
Energy-Efficient Classification: Adaptive Approach (2017) (0)
Robust strategies for cooperative and cognitive wireless communication systems (2009) (0)
Online Selective Classification with Limited Feedback (2021) (0)
Smart Distributed Sensor Fields: Algorithms for Tactical Sensors (2013) (0)
Technical Committee on Networks and Communication Systems [Technical Activities] (2016) (0)
Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction (2023) (0)
Sparsity penalized reconstruction framework for broadband dispersion extraction (2010) (0)
Ju l 2 01 6 Remember the Curse of Dimensionality : The Case of Goodness-ofFit Testing in Arbitrary Dimension (2016) (0)

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What Schools Are Affiliated With Venkatesh C. Saligrama?

Venkatesh C. Saligrama is affiliated with the following schools:

West Virginia University

Venkatesh C. Saligrama's Academic­Influence.com Rankings

Why Is Venkatesh C. Saligrama Influential?

Venkatesh C. Saligrama's Published Works

Published Works

What Schools Are Affiliated With Venkatesh C. Saligrama?

Venkatesh C. Saligrama's AcademicInfluence.com Rankings