Venkatesh Saligrama

发表

Crowdsourcing with Sparsely Interacting Workers pdf

Venkatesh Saligrama, Csaba Szepesvári, Yao Ma, 2017, ArXiv.

On sensing capacity of sensor networks for a class of linear observation models

Venkatesh Saligrama, S. Aeron, M. Zhao, 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

Thresholded Basis Pursuit: Quantizing Linear Programming Solutions for Optimal Support Recovery and Approximation in Compressed Sensing pdf

Venkatesh Saligrama, Manqi Zhao, Venkatesh Saligrama, 2008, ArXiv.

A Topic Modeling Approach to Rank Aggregation

Venkatesh Saligrama, P. Ishwar, Weicong Ding, 2014 .

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings

Adam Tauman Kalai, Venkatesh Saligrama, Tolga Bolukbasi, 2016, NIPS.

Outlier detection via localized p-value estimation

Venkatesh Saligrama, M. Zhao, M. Zhao, 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

A Mutual Information Characterization for Sparse Signal Processing

George K. Atia, Venkatesh Saligrama, 2011 .

Remember the curse of dimensionality: the case of goodness-of-fit testing in arbitrary dimension

E. Arias-Castro, Venkatesh Saligrama, Bruno Pelletier, 2016, 1607.08156.

Information Theoretic Bounds for Compressed Sensing

Venkatesh Saligrama, Shuchin Aeron, Manqi Zhao, 2008, IEEE Transactions on Information Theory.

Algorithms and bounds for sensing capacity and compressed sensing with applications to learning graphical models

Venkatesh Saligrama, S. Aeron, M. Zhao, 2008, 2008 Information Theory and Applications Workshop.

Unsupervised Sequential Sensor Acquisition

Venkatesh Saligrama, Csaba Szepesvári, Manjesh Kumar Hanawal, 2017, AISTATS.

Shallow RNNs: A Method for Accurate Time-series Classification on Tiny Devices

Vinu Sankar Sadasivan, Prateek Jain, H. Simhadri, 2019 .

Machine learning combining CT findings and clinical parameters improves prediction of length of stay and ICU admission in torso trauma

Venkatesh Saligrama, S. Anderson, J. Scalera, 2021, European Radiology.

Energy-Efficient Classification: Adaptive Approach

Venkatesh Saligrama, A. Joshi, Zafar Takhirov, 2017 .

Minimax Rank-1 Factorization

Alexander Olshevsky, Venkatesh Saligrama, J. Hendrickx, 2019 .

PRISM: Person Reidentification via Structured Matching

Ziming Zhang, Venkatesh Saligrama, 2014, IEEE Transactions on Circuits and Systems for Video Technology.

Most large topic models are approximately separable

Venkatesh Saligrama, Prakash Ishwar, Weicong Ding, 2015, 2015 Information Theory and Applications Workshop (ITA).

Abnormal events detection based on spatio-temporal co-occurences

Christophe Rosenberger, Venkatesh Saligrama, Pierre-Marc Jodoin, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

Video Anomaly Identification [ a Statistical Approach ]

Venkatesh Saligrama, Pierre-Marc Jodoin, Janusz Konrad, 2022 .

Unique contributions of parvalbumin and cholinergic interneurons in organizing striatal networks during movement

Venkatesh Saligrama, Dana Zemel, Xue Han, 2019, Nature Neuroscience.

Minimax Rate for Learning From Pairwise Comparisons

Alexander Olshevsky, Venkatesh Saligrama, J. Hendrickx, 2019 .

Mild Blast Injury Produces Acute Changes in Basal Intracellular Calcium Levels and Activity Patterns in Mouse Hippocampal Neurons.

Kyle R. Hansen, X. Han, Venkatesh Saligrama, 2018, Journal of neurotrauma.

Spectral Clustering with Unbalanced Data

Venkatesh Saligrama, Venkatesh Saligrama, Jing Qian, 2013, 1302.5134.

Ju l 2 01 6 Remember the Curse of Dimensionality : The Case of Goodness-ofFit Testing in Arbitrary Dimension

E. Arias-Castro, Venkatesh Saligrama, Bruno Pelletier, 2016 .

Abnormal events detection based on spatio-temporal co-occurences

Christophe Rosenberger, Venkatesh Saligrama, Pierre-Marc Jodoin, 2009, CVPR.

Markov group testing

D. Castañón, Venkatesh Saligrama, Joseph Wang, 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

( SPECIAL SECTION - DISTRIBUTED SIGNAL PROCESSING IN SENSOR NETWORKS )

Rabab K. Ward, Petar M. Djuric, Ling Guan, 2006 .

A Rank-SVM Approach to Anomaly Detection

Venkatesh Saligrama, Jing Qian, J. Root, 2014, 1405.0530.

Faster Convex Lipschitz Regression via 2-block ADMM

B. Kulis, Venkatesh Saligrama, Ali Siahkamari, 2021, ArXiv.

Faster Algorithms for Learning Convex Functions

B. Kulis, Venkatesh Saligrama, Ali Siahkamari, 2021, 2111.01348.

Person Re-identification via Structured Prediction pdf

Venkatesh Saligrama, Ziming Zhang, Ziming Zhang, 2014, ArXiv.

Identification of uncertain systems described by linear fractional transformations

Venkatesh Saligrama, 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

Fine-grained Few-shot Recognition by Deep Object Parsing

Venkatesh Saligrama, Ruizhao Zhu, Samarth Mishra, 2022, 2207.07110.

How Transferable are Video Representations Based on Synthetic Data?

A. Oliva, Kate Saenko, Hilde Kuehne, 2022, NeurIPS.

Effectively Leveraging Attributes for Visual Similarity

Bryan A. Plummer, Venkatesh Saligrama, Ranjitha Kumar, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Guest Editorial Inference and Learning over Networks

Cédric Richard, Ali H. Sayed, Venkatesh Saligrama, 2016, IEEE Trans. Signal Inf. Process. over Networks.

Distributed Field Estimation with One–bit Sensors

Venkatesh Saligrama, Ye Wang, Prakash Ishwar, 2008 .

Necessary and sufficient conditions for robust identification of uncertain LTI systems

Venkatesh Saligrama, Venkatesh Saligrama, 2004, Syst. Control. Lett..

Sparsity penalized reconstruction framework for broadband dispersion extraction

Venkatesh Saligrama, Shuchin Aeron, Sandip Bose, 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

Sensing and reconstruction of sparse phenomena bounds and algorithms

Venkatesh Saligrama, S. Aeron, 2009 .

RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?

Venkatesh Saligrama, Ziming Zhang, Anil Kag, 2019, ICLR.

Condensing CNNs with Partial Differential Equations

Venkatesh Saligrama, Anil Kag, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Online Selective Classification with Limited Feedback pdf

Venkatesh Saligrama, Aditya Gangrade, Anil Kag, 2021, NeurIPS.

A combined approach to multi-label multi-task learning

Venkatesh Saligrama, David A. Castañón, Delaram Motamedvaziri, 2012, 2012 IEEE Statistical Signal Processing Workshop (SSP).

Distributed Detection in Sensor Networks with Limited Range Sensors pdf

Venkatesh Saligrama, Erhan Baki Ermis, Venkatesh Saligrama, 2007, ArXiv.

An Information-Theoretic Approach for Sparse Recovery with Linear and Nonlinear Observations

Cem Aksoylar, Venkatesh Saligrama, George K. Atia, 2016 .

Fine-grained Few-shot Recognition by Deep Object Parsing

Venkatesh Saligrama, Ruizhao Zhu, Samarth Mishra, 2022, ArXiv.

FedHeN: Federated Learning in Heterogeneous Networks

Venkatesh Saligrama, D. A. Acar, 2022, ArXiv.

A Doubly Optimistic Strategy for Safe Linear Bandits

Venkatesh Saligrama, Aditya Gangrade, Tianrui Chen, 2022, ArXiv.

Learning to Approximate a Bregman Divergence

Venkatesh Saligrama, Brian Kulis, Ali Siahkamari, 2020, NeurIPS.

Learning Bregman Divergences pdf

Venkatesh Saligrama, David A. Castanon, Brian Kulis, 2019, ArXiv.

Local Anomaly Detection

Venkatesh Saligrama, Manqi Zhao, Venkatesh Saligrama, 2012, AISTATS.

Venkatesh Saligrama, Joseph Wang, David A. Castañón, 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Don’t Even Look Once: Synthesizing Features for Zero-Shot Detection

Venkatesh Saligrama, Hanxiao Wang, Pengkai Zhu, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Zero Shot Detection

Venkatesh Saligrama, Hanxiao Wang, Pengkai Zhu, 2018, IEEE Transactions on Circuits and Systems for Video Technology.

Experimental realization of long-distance entanglement between spins in antiferromagnetic quantum spin chains

V. Saligrama, Venkatesh Saligrama, A. Revcolevschi, 2015, Nature Physics.

Adaptive Neural Networks for Efficient Inference

Venkatesh Saligrama, Joseph Wang, Tolga Bolukbasi, 2017, ICML.

Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models

Venkatesh Saligrama, Aditya Gangrade, Bobak Nazer, 2019, NeurIPS.

Testing Changes in Communities for the Stochastic Block Model pdf

Venkatesh Saligrama, Aditya Gangrade, Bobak Nazer, 2018, ArXiv.

Clustering and Community Detection With Imbalanced Clusters

Cem Aksoylar, Venkatesh Saligrama, Jing Qian, 2016, IEEE Transactions on Signal and Information Processing over Networks.

Sensing structure in learning-based binary classification of high-dimensional data

Venkatesh Saligrama, W. Clem Karl, Prakash Ishwar, 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Distributed Detection in Sensor Networks With Limited Range Multimodal Sensors

Venkatesh Saligrama, Erhan Baki Ermis, Venkatesh Saligrama, 2007, IEEE Transactions on Signal Processing.

Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena

Venkatesh Saligrama, Erhan Baki Ermis, Venkatesh Saligrama, 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

A gene filter for comparative analysis of single-cell RNA-sequencing trajectory datasets

Venkatesh Saligrama, Laura Balzano, Yutong Wang, 2019, bioRxiv.

Spectral clustering with imbalanced data

Venkatesh Saligrama, Jing Qian, Venkatesh Saligrama, 2013, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Graph-based Learning with Unbalanced Clusters pdf

Venkatesh Saligrama, Jing Qian, Manqi Zhao, 2012, ArXiv.

Graph Construction for Learning with Unbalanced Data

Venkatesh Saligrama, Manqi Zhao, Venkatesh Saligrama, 2011, 1112.2319.

Anomaly Detection with Score functions based on Nearest Neighbor Graphs

Venkatesh Saligrama, Manqi Zhao, Venkatesh Saligrama, 2009, NIPS.

Boolean Compressed Sensing and Noisy Group Testing

George Atia, Venkatesh Saligrama, George K. Atia, 2009, IEEE Transactions on Information Theory.

Minimax Rate for Learning From Pairwise Comparisons in the BTL Model

Venkatesh Saligrama, Alex Olshevsky, Julien Hendrickx, 2020, ICML.

Graph Resistance and Learning from Pairwise Comparisons

Venkatesh Saligrama, Julien M. Hendrickx, Alexander Olshevsky, 2019, ICML.

Prediction of hospitalization due to heart diseases by supervised learning methods

Venkatesh Saligrama, Ioannis Ch. Paschalidis, Theodora S. Brisimi, 2015, Int. J. Medical Informatics.

Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms

Venkatesh Saligrama, Pak Hou Che, Sidharth Jaggi, 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Motion detection with an unstable camera

Venkatesh Saligrama, Pierre-Marc Jodoin, Janusz Konrad, 2008, 2008 15th IEEE International Conference on Image Processing.

Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data

Cheng Perng Phoo, R. Feris, Venkatesh Saligrama, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Piecewise Linear Regression via a Difference of Convex Functions

B. Kulis, Venkatesh Saligrama, Ali Siahkamari, 2020, ICML.

Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data pdf

Cem Aksoylar, Venkatesh Saligrama, Venkatesh Saligrama, 2014, ArXiv.

Zero-Shot Learning via Semantic Similarity Embedding

Venkatesh Saligrama, Ziming Zhang, Ziming Zhang, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

One-Bit Distributed Sensing and Coding for Field Estimation in Sensor Networks

Venkatesh Saligrama, Ye Wang, Prakash Ishwar, 2007, IEEE Transactions on Signal Processing.

On Universal Distributed Estimation of Noisy Fields with One-bit Sensors

Venkatesh Saligrama, Ye Wang, Prakash Ishwar, 2007 .

Effectively Leveraging Attributes for Visual Similarity

Venkatesh Saligrama, Bryan A. Plummer, Ranjitha Kumar, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Multi-stage classifier design

Venkatesh Saligrama, Kirill Trapeznikov, David A. Castañón, 2012, Machine Learning.

Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency pdf

Kate Saenko, Venkatesh Saligrama, Samarth Mishra, 2021, BMVC.

Stem surface roughness alters creep induced subsidence and 'taper-lock' in a cemented femoral hip prosthesis.

Venkatesh Saligrama, J. Blaha, T. Gruen, 2001, Journal of biomechanics.

A Provably Efficient Algorithm for Separable Topic Discovery

Venkatesh Saligrama, Prakash Ishwar, Weicong Ding, 2016, IEEE Journal of Selected Topics in Signal Processing.

Behavior Subtraction

Venkatesh Saligrama, Pierre-Marc Jodoin, Janusz Konrad, 2009, IEEE Transactions on Image Processing.

Limits on Testing Structural Changes in Ising Models pdf

Venkatesh Saligrama, Aditya Gangrade, Bobak Nazer, 2020, NeurIPS.

Activity Based Matching in Distributed Camera Networks

Venkatesh Saligrama, Pierre Clarot, Erhan Baki Ermis, 2010, IEEE Transactions on Image Processing.

Federated Learning Based on Dynamic Regularization pdf

Venkatesh Saligrama, Matthew Mattina, Paul N. Whatmough, 2021, ICLR.

Debiasing Model Updates for Improving Personalized Federated Training

Venkatesh Saligrama, Matthew Mattina, Paul N. Whatmough, 2021, ICML.

Memory Efficient Online Meta Learning

Venkatesh Saligrama, Ruizhao Zhu, Durmus Alp Emre Acar, 2021, ICML.

Training Recurrent Neural Networks via Forward Propagation Through Time

Venkatesh Saligrama, Anil Kag, Venkatesh Saligrama, 2021, ICML.

Foreground-Adaptive Background Subtraction

Venkatesh Saligrama, Pierre-Marc Jodoin, Janusz Konrad, 2009, IEEE Signal Processing Letters.

Video anomaly detection based on local statistical aggregates

Venkatesh Saligrama, Zhu Chen, Venkatesh Saligrama, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Learning Classifiers for Target Domain with Limited or No Labels

Venkatesh Saligrama, Hanxiao Wang, Pengkai Zhu, 2019, ICML.

Learning Compositional Representations for Effective Low-Shot Generalization

Venkatesh Saligrama, Samarth Mishra, Pengkai Zhu, 2022, IEEE transactions on pattern analysis and machine intelligence.

Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs pdf

Venkatesh Saligrama, Jing Qian, Jonathan Root, 2016, ArXiv.

New statistic in P-value estimation for anomaly detection

Venkatesh Saligrama, Jing Qian, Venkatesh Saligrama, 2012, 2012 IEEE Statistical Signal Processing Workshop (SSP).

Zero-Shot Learning via Joint Latent Similarity Embedding

Venkatesh Saligrama, Ziming Zhang, Ziming Zhang, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Modal Participation Analysis for Identifying Brake Squeal Mechanism

Shih-Wei Kung, Venkatesh C. Saligrama, Michael A. Riehle, 2000 .

Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers

Venkatesh Saligrama, Csaba Szepesvári, Alexander Olshevsky, 2018, ICML.

Abnormality detection using low-level co-occurring events

Venkatesh Saligrama, Pierre-Marc Jodoin, Yannick Benezeth, 2011, Pattern Recognit. Lett..

On compressed blind de-convolution of filtered sparse processes

Venkatesh Saligrama, Manqi Zhao, Venkatesh Saligrama, 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

Rapid: Rapidly accelerated proximal gradient algorithms for convex minimization

Venkatesh Saligrama, Ziming Zhang, Ziming Zhang, 2014, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Generalized Zero-Shot Recognition Based on Visually Semantic Embedding

Venkatesh Saligrama, Hanxiao Wang, Pengkai Zhu, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Learning Joint Feature Adaptation for Zero-Shot Recognition pdf

Venkatesh Saligrama, Ziming Zhang, Ziming Zhang, 2016, ArXiv.

Video Anomaly Identification

Venkatesh Saligrama, Pierre-Marc Jodoin, Janusz Konrad, 2010, IEEE Signal Processing Magazine.

Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction

Venkatesh Saligrama, Joseph Wang, Kirill Trapeznikov, 2015, NIPS.

Modeling Patterns of Activity and Detecting Abnormal Events with Low-Level Co-occurrences

Venkatesh Saligrama, Pierre-Marc Jodoin, Yannick Benezeth, 2011 .

Adaptive Neural Networks for Fast Test-Time Prediction pdf

Venkatesh Saligrama, Joseph Wang, Tolga Bolukbasi, 2017, ArXiv.

An impossibility result for high dimensional supervised learning

Venkatesh Saligrama, W. Clem Karl, Prakash Ishwar, 2013, 2013 IEEE Information Theory Workshop (ITW).

Crime and Punishment for Cognitive Radios

A. Sahai, V. Saligrama, G. Atia, 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

Probabilistic Semantic Retrieval for Surveillance Videos With Activity Graphs

Venkatesh Saligrama, Joseph Wang, Yuting Chen, 2017, IEEE Transactions on Multimedia.

A new algorithm for outlier rejection in particle filters

Venkatesh Saligrama, Rohit Kumar, Erhan Baki Ermis, 2010, 2010 13th International Conference on Information Fusion.

Locally-Linear Learning Machines (L3M)

Venkatesh Saligrama, Joseph Wang, Venkatesh Saligrama, 2013, ACML.

Broadband Dispersion Extraction Using Simultaneous Sparse Penalization

Venkatesh Saligrama, Shuchin Aeron, Sandip Bose, 2011, IEEE Transactions on Signal Processing.

Axisymmetric finite element analysis of a debonded total hip stem with an unsupported distal tip.

Venkatesh Saligrama, J. Blaha, T. Gruen, 1993, Journal of biomechanical engineering.

Sequential Optimization for Efficient High-Quality Object Proposal Generation

Venkatesh Saligrama, Philip H. S. Torr, Ziming Zhang, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

BING++: A Fast High Quality Object Proposal Generator at 100fps pdf

Venkatesh Saligrama, Tolga Bolukbasi, Yun Liu, 2015, ArXiv.

Implicit Active-Contouring with MRF

Venkatesh Saligrama, Pierre-Marc Jodoin, Janusz Konrad, 2009, ICIAR.

Group Membership Prediction

Venkatesh Saligrama, Ziming Zhang, Yuting Chen, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Efficient Sensor Management Policies for Distributed Target Tracking in Multihop Sensor Networks

Venkatesh Saligrama, David A. Castañón, Shuchin Aeron, 2008, IEEE Transactions on Signal Processing.

Non-adaptive group testing: Explicit bounds and novel algorithms

Venkatesh Saligrama, Sidharth Jaggi, Chun Lam Chan, 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

Pruning Random Forests for Prediction on a Budget

Venkatesh Saligrama, Joseph Wang, Feng Nan, 2016, NIPS.

Feature-Budgeted Random Forest

Venkatesh Saligrama, Joseph Wang, Feng Nan, 2015, ICML.

Supervised Sequential Classification Under Budget Constraints

Venkatesh Saligrama, Kirill Trapeznikov, Venkatesh Saligrama, 2013, AISTATS.

On Optimal Outage in Relay Channels With General Fading Distributions

George Atia, Venkatesh Saligrama, Masoud Sharif, 2007, IEEE Transactions on Information Theory.

Sparse signal recovery under poisson statistics for online marketing applications

Venkatesh Saligrama, Mohammad H. Rohban, Delaram Motamedvaziri, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Sparse signal recovery under Poisson statistics

Venkatesh Saligrama, Mohammad H. Rohban, Delaram Motamedvaziri, 2013, 2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Bayesian filtering without an observation model

Venkatesh Saligrama, Sanjoy K. Mitter, Peter Jones, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Quantifying and Reducing Stereotypes in Word Embeddings pdf

Adam Tauman Kalai, Venkatesh Saligrama, Tolga Bolukbasi, 2016, ArXiv.

Cost effective algorithms for spectral bandits

Venkatesh Saligrama, Manjesh Kumar Hanawal, Venkatesh Saligrama, 2015, 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Graph-Constrained Group Testing

Amin Karbasi, Venkatesh Saligrama, Soheil Mohajer, 2010, IEEE Transactions on Information Theory.

Thresholded Basis Pursuit: Support Recovery for Sparse and Approximately Sparse Signals

Venkatesh Saligrama, Manqi Zhao, Venkatesh Saligrama, 2008 .

Thresholded Basis Pursuit: An LP Algorithm for Achieving Optimal Support Recovery for Sparse and Approximately Sparse Signals from Noisy Random Measurements

V. Saligrama, M. Zhao, Venkatesh Saligrama, 2008, 0809.4883.

Information theoretic bounds to performance of Compressed Sensing and Sensor Networks

Venkatesh Saligrama, Shuchin Aeron, Manqi Zhao, 2008 .

Spectrum Enforcement and Liability Assignment in Cognitive Radio Systems

A. Sahai, V. Saligrama, G. Atia, 2008, 2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks.

RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?

Venkatesh Saligrama, Ziming Zhang, Anil Kag, 2019, 1908.08574.

Time Adaptive Recurrent Neural Network

Venkatesh Saligrama, Anil Kag, Venkatesh Saligrama, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Efficient Training of Very Deep Neural Networks for Supervised Hashing

Venkatesh Saligrama, Ziming Zhang, Yuting Chen, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Local Supervised Learning through Space Partitioning

Venkatesh Saligrama, Joseph Wang, Venkatesh Saligrama, 2012, NIPS.

A new one-class SVM for anomaly detection

Venkatesh Saligrama, Jing Qian, Yuting Chen, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Retrieval in Long-Surveillance Videos Using User-Described Motion and Object Attributes

Venkatesh Saligrama, Pierre-Marc Jodoin, Mohamed A. Elgharib, 2014, IEEE Transactions on Circuits and Systems for Video Technology.

Bandit Quickest Changepoint Detection

Venkatesh Saligrama, Aditya Gopalan, Braghadeesh Lakshminarayanan, 2021, NeurIPS.

Connected Sub-graph Detection

Venkatesh Saligrama, Jing Qian, Yuting Chen, 2014, AISTATS.

Cheap Bandits pdf

Venkatesh Saligrama, Rémi Munos, Michal Valko, 2015, ICML.

Algorithms for Linear Bandits on Polyhedral Sets pdf

Venkatesh Saligrama, Amir Leshem, Manjesh Kumar Hanawal, 2015, ArXiv.

Active Boosted Learning (ActBoost)

Venkatesh Saligrama, Kirill Trapeznikov, David A. Castañón, 2011, AISTATS.

ActiveHedge: Hedge meets Active Learning

Jacob D. Abernethy, Venkatesh Saligrama, Bhuvesh Kumar, 2022, ICML.

" Active Boosted Learning "

D. Castañón, Venkatesh Saligrama, K. Trapeznikov, 2016 .

"active Boosted Learning" Active Boosted Learning (actboost)

D. Castañón, Venkatesh Saligrama, K. Trapeznikov, 2016 .

Connected Subgraph Detection with Mirror Descent on SDPs

Cem Aksoylar, Venkatesh Saligrama, Lorenzo Orecchia, 2017, ICML.

Efficient Minimax Signal Detection on Graphs

Venkatesh Saligrama, Jing Qian, Venkatesh Saligrama, 2014, NIPS.

Anomalous cluster detection

Venkatesh Saligrama, Jing Qian, Yuting Chen, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Causal Inference for Time Series: A Linear Systems Approach

Venkatesh Saligrama, P. Shah, 2017 .

A multi-resolution approach for discovery and 3-D modeling of archaeological sites using satellite imagery and a UAV-borne camera

Venkatesh Saligrama, Joseph Wang, Mac Schwager, 2016, 2016 American Control Conference (ACC).

Zero-Shot Recognition via Structured Prediction

Venkatesh Saligrama, Ziming Zhang, Ziming Zhang, 2016, ECCV.

Networked sensing information and control

Venkatesh Saligrama, Venkatesh Saligrama, 2008 .

Distributed Detection in Sensor Networks With Packet Losses and Finite Capacity Links

M. Alanyali, V. Saligrama, O. Savas, 2006, IEEE Transactions on Signal Processing.

Deterministic Designs with Deterministic Guarantees: Toeplitz Compressed Sensing Matrices, Sequence Designs and System Identification pdf

Venkatesh Saligrama, Venkatesh Saligrama, Venkatesh Saligrama, 2008, ArXiv.

Aperiodic Sequences With Uniformly Decaying Correlations With Applications to Compressed Sensing and System Identification

Venkatesh Saligrama, Venkatesh Saligrama, 2012, IEEE Transactions on Information Theory.

Noisy group testing: An information theoretic perspective

George Atia, Venkatesh Saligrama, George K. Atia, 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Probabilistic Belief Revision with Structural Constraints

Venkatesh Saligrama, Sanjoy K. Mitter, Peter Jones, 2010, NIPS.

Revision of marginal probability assessments

Venkatesh Saligrama, Sanjoy K. Mitter, Peter Jones, 2010, 2010 13th International Conference on Information Fusion.

Reliable Distributed Estimation with Intermittent Communications

V. Saligrama, D.A. Castanon, D. Castañón, 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

Efficient Distributed Topic Modeling with Provable Guarantees

Venkatesh Saligrama, Prakash Ishwar, Weicong Ding, 2014, AISTATS.

Dynamic topic discovery through sequential projections

Venkatesh Saligrama, Prakash Ishwar, Weicong Ding, 2013, 2013 Asilomar Conference on Signals, Systems and Computers.

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”

Venkatesh Saligrama, Feng Nan, Venkatesh Saligrama, 2017, IEEE Transactions on Information Theory.

Selective Classification via One-Sided Prediction

Venkatesh Saligrama, Anil Kag, Aditya Gangrade, 2020, AISTATS.

RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm pdf

Venkatesh Saligrama, Ming Li, Ziming Zhang, 2020, 2020 25th International Conference on Pattern Recognition (ICPR).

RNNs Evolving in Equilibrium: A Solution to the Vanishing and Exploding Gradients pdf

Venkatesh Saligrama, Ziming Zhang, Anil Kag, 2019, ArXiv.

Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds

Venkatesh Saligrama, Aditya Gangrade, Bobak Nazer, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Budget Learning via Bracketing pdf

Venkatesh Saligrama, Aditya Gangrade, Durmus Alp Emre Acar, 2020, AISTATS.

Efficient algorithms for linear polyhedral bandits

Venkatesh Saligrama, Amir Leshem, Manjesh Kumar Hanawal, 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Cost aware Inference for IoT Devices

Venkatesh Saligrama, Nan Feng, Prateek Jain, 2019, AISTATS.

A technical framework for light- handed regulation of cognitive radios

George Atia, Venkatesh Saligrama, Anant Sahai, 2009, IEEE Communications Magazine.

Codes to unmask spectrum violators in cognitive radio systems

A. Sahai, V. Saligrama, G. Atia, 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

Robust Energy Efficient Cooperative Spectrum Sensing in Cognitive Radios

George Atia, Venkatesh Saligrama, George K. Atia, 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

Learning Efficient Anomaly Detectors from K-NN Graphs pdf

Venkatesh Saligrama, Jing Qian, Jonathan Root, 2015, AISTATS.

Learning to Drive Anywhere

Eshed Ohn-Bar, Venkatesh Saligrama, Ruizhao Zhu, 2023, ArXiv.

Mild Blast Injury Produces Acute Changes in Basal Intracellular Calcium Levels and Activity Patterns in Mouse Hippocampal Neurons.

Kyle R. Hansen, Venkatesh Saligrama, W. Eldred, 2018, Journal of neurotrauma.

Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk

Venkatesh Saligrama, Aditya Gangrade, Tianrui Chen, 2022, ICML.

Distributed Tracking in Multihop Sensor Networks With Communication Delays

Venkatesh Saligrama, Murat Alanyali, R. Rahman, 2007, IEEE Transactions on Signal Processing.

Sensor Selection by Linear Programming pdf

Venkatesh Saligrama, Joseph Wang, Kirill Trapeznikov, 2015, ArXiv.

Sparse signal processing with linear and non-linear observations: A unified shannon theoretic approach

George K. Atia, Venkatesh Saligrama, Cem Aksoylar, 2013, 2013 IEEE Information Theory Workshop (ITW).

Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction

Venkatesh Saligrama, Chen Chen, D. Walker, 2023, arXiv.org.

Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the “What” and Focus on the “How”!

Venkatesh Saligrama, Dylan Walker, Chen Chen, 2023, Annual Meeting of the Association for Computational Linguistics.

Non-adaptive group testing with inhibitors

Sidharth Jaggi, Venkatesh Saligrama, Abhinav Ganesan, 2014, 2015 IEEE Information Theory Workshop (ITW).

Adaptive Classification for Prediction Under a Budget

Venkatesh Saligrama, Feng Nan, Venkatesh Saligrama, 2017, NIPS.

Scaffolding a Student to Instill Knowledge

Venkatesh Saligrama, D. A. Acar, Anil Kag, 2023, ICLR.

Minimax Optimal Sparse Signal Recovery With Poisson Statistics

Venkatesh Saligrama, Mohammad H. Rohban, Delaram Motamed Vaziri, 2015, IEEE Transactions on Signal Processing.

Field of Groves: An Energy-Efficient Random Forest pdf

Venkatesh Saligrama, Joseph Wang, Zafar Takhirov, 2017, ArXiv.

Ieee Transaction on Pattern Analysis and Machine Intelligence 1 Sequential Optimization for Efficient High-quality Object Proposal Generation

Philip H. S. Torr, Xi Chen, Ming-Ming Cheng, 2022 .

Learning to Approximate a Bregman Divergence

D. Castañón, Venkatesh Saligrama, Xide Xia, 2020, NeurIPS.

Sensing-aware kernel SVM

Venkatesh Saligrama, W. Clem Karl, Prakash Ishwar, 2013, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Wireless Ad Hoc Networks: Strategies and Scaling Laws for the Fixed SNR Regime

Venkatesh Saligrama, Shuchin Aeron, Venkatesh Saligrama, 2006, IEEE Transactions on Information Theory.

Fine-grained Few-shot Recognition by Deep Object Parsing

Venkatesh Saligrama, Ruizhao Zhu, Samarth Mishra, 2022, BMVC.

Prediction of hospitalization due to heart diseases by supervised learning methods

Theodora S. Brisimi, I. Paschalidis, Venkatesh Saligrama, 2015, Int. J. Medical Informatics.