| 2026 | ACL | DeepFact: Co-Evolving Benchmarks and Agents for Deep Research Factuality. | Yukun Huang, Leonardo F. R. Ribeiro, Momchil Hardalov, Bhuwan Dhingra, Markus Dreyer, Venkatesh Saligrama |
| 2026 | EACL | Hearing Between the Lines: Unlocking the Reasoning Power of LLMs for Speech Evaluation. | Arjun Chandra, Kevin Miller, Venkatesh Ravichandran, Constantinos Papayiannis, Venkatesh Saligrama |
| 2025 | CVPR | SPARC: Score Prompting and Adaptive Fusion for Zero-Shot Multi-Label Recognition in Vision-Language Models. | Kevin Miller, Aditya Gangrade, Samarth Mishra, Kate Saenko, Venkatesh Saligrama |
| 2025 | EMNLP | Scaling Up Temporal Domain Generalization via Temporal Experts Averaging. | Aoming Liu, Kevin Miller, Venkatesh Saligrama, Kate Saenko, Boqing Gong, Ser-Nam Lim, Bryan A. Plummer |
| 2025 | ICCV | SCRAMBLe: Enhancing Multimodal LLM Compositionality with Synthetic Preference Data. | Samarth Mishra, Kate Saenko, Venkatesh Saligrama |
| 2025 | ICCV | BabyVLM: Data-Efficient Pretraining of VLMs Inspired by Infant Learning. | Shengao Wang Boston University, Arjun Chandra, Aoming Liu, Venkatesh Saligrama, Boqing Gong |
| 2025 | ICLR | GPS: A Probabilistic Distributional Similarity with Gumbel Priors for Set-to-Set Matching. | Ziming Zhang, Fangzhou Lin, Haotian Liu, Jose Morales, Haichong Zhang, Kazunori D. Yamada, Vijaya B. Kolachalama, Venkatesh Saligrama |
| 2025 | ICML | Feasible Action Search for Bandit Linear Programs via Thompson Sampling. | Aditya Gangrade, Aldo Pacchiano, Clayton Scott, Venkatesh Saligrama |
| 2024 | COLT | Safe Linear Bandits over Unknown Polytopes. | Aditya Gangrade, Tianrui Chen, Venkatesh Saligrama |
| 2024 | ICML | Testing the Feasibility of Linear Programs with Bandit Feedback. | Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama, Clayton Scott |
| 2023 | ACL | Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the "What" and Focus on the "How"! | Chen Chen, Dylan Walker, Venkatesh Saligrama |
| 2023 | BMVC | Fine-grained Few-shot Recognition by Deep Object Parsing. | Ruizhao Zhu, Pengkai Zhu, Samarth Mishra, Venkatesh Saligrama |
| 2023 | CoRL | Learning to Drive Anywhere. | Ruizhao Zhu, Peng Huang, Eshed Ohn-Bar, Venkatesh Saligrama |
| 2023 | ICLR | Scaffolding a Student to Instill Knowledge. | Anil Kag, Durmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama |
| 2023 | ICLR | Efficient Edge Inference by Selective Query. | Anil Kag, Igor Fedorov, Aditya Gangrade, Paul N. Whatmough, Venkatesh Saligrama |
| 2022 | CVPR | Condensing CNNs with Partial Differential Equations. | Anil Kag, Venkatesh Saligrama |
| 2022 | CVPR | Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data. | Samarth Mishra, Rameswar Panda, Cheng Perng Phoo, Chun-Fu Richard Chen, Leonid Karlinsky, Kate Saenko, Venkatesh Saligrama, Rogrio Schmidt Feris |
| 2022 | ICML | Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. | Tianrui Chen, Aditya Gangrade, Venkatesh Saligrama |
| 2022 | ICML | ActiveHedge: Hedge meets Active Learning. | Bhuvesh Kumar, Jacob D. Abernethy, Venkatesh Saligrama |
| 2022 | ICML | Faster Algorithms for Learning Convex Functions. | Ali Siahkamari, Durmus Alp Emre Acar, Christopher Liao, Kelly L. Geyer, Venkatesh Saligrama, Brian Kulis |
| 2021 | AISTATS | Selective Classification via One-Sided Prediction. | Aditya Gangrade, Anil Kag, Venkatesh Saligrama |
| 2021 | BMVC | Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. | Samarth Mishra, Kate Saenko, Venkatesh Saligrama |
| 2021 | CVPR | Time Adaptive Recurrent Neural Network. | Anil Kag, Venkatesh Saligrama |
| 2021 | CVPR | Effectively Leveraging Attributes for Visual Similarity. | Samarth Mishra, Zhongping Zhang, Yuan Shen, Ranjitha Kumar, Venkatesh Saligrama, Bryan A. Plummer |
| 2021 | ICCV | Effectively Leveraging Attributes for Visual Similarity. | Samarth Mishra, Zhongping Zhang, Yuan Shen, Ranjitha Kumar, Venkatesh Saligrama, Bryan A. Plummer |
| 2021 | ICLR | Federated Learning Based on Dynamic Regularization. | Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama |
| 2021 | ICML | Memory Efficient Online Meta Learning. | Durmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama |
| 2021 | ICML | Debiasing Model Updates for Improving Personalized Federated Training. | Durmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama |
| 2021 | ICML | Training Recurrent Neural Networks via Forward Propagation Through Time. | Anil Kag, Venkatesh Saligrama |
| 2020 | AISTATS | Budget Learning via Bracketing. | Durmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama |
| 2020 | AISTATS | Minimax Rank-$1$ Matrix Factorization. | Venkatesh Saligrama, Alexander Olshevsky, Julien M. Hendrickx |
| 2020 | CVPR | Don't Even Look Once: Synthesizing Features for Zero-Shot Detection. | Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama |
| 2020 | ICLR | RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? | Anil Kag, Ziming Zhang, Venkatesh Saligrama |
| 2020 | ICML | Minimax Rate for Learning From Pairwise Comparisons in the BTL Model. | Julien M. Hendrickx, Alex Olshevsky, Venkatesh Saligrama |
| 2020 | ICML | Piecewise Linear Regression via a Difference of Convex Functions. | Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama |
| 2020 | ICPR | RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. | Yun Yue, Ming Li, Venkatesh Saligrama, Ziming Zhang |
| 2020 | ICPR | Low Dimensional Visual Attributes: An Interpretable Image Encoding. | Pengkai Zhu, Ruizhao Zhu, Samarth Mishra, Venkatesh Saligrama |
| 2019 | AISTATS | Online Algorithm for Unsupervised Sensor Selection. | Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvri, Venkatesh Saligrama |
| 2019 | AISTATS | Cost aware Inference for IoT Devices. | Pengkai Zhu, Durmus Alp Emre Acar, Nan Feng, Prateek Jain, Venkatesh Saligrama |
| 2019 | CVPR | Generalized Zero-Shot Recognition Based on Visually Semantic Embedding. | Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama |
| 2019 | EMNLP | Robust Text Classifier on Test-Time Budgets. | Md. Rizwan Parvez, Tolga Bolukbasi, Kai-Wei Chang, Venkatesh Saligrama |
| 2019 | ICCV | Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations. | Hanxiao Wang, Venkatesh Saligrama, Stan Sclaroff, Vitaly Ablavsky |
| 2019 | ICML | Graph Resistance and Learning from Pairwise Comparisons. | Julien M. Hendrickx, Alexander Olshevsky, Venkatesh Saligrama |
| 2019 | ICML | Learning Classifiers for Target Domain with Limited or No Labels. | Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama |
| 2018 | ICASSP | Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds. | Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama |
| 2018 | ICML | Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. | Yao Ma, Alexander Olshevsky, Csaba Szepesvri, Venkatesh Saligrama |
| 2017 | AAAI | Resource Constrained Structured Prediction. | Tolga Bolukbasi, Kai-Wei Chang, Joseph Wang, Venkatesh Saligrama |
| 2017 | AISTATS | Unsupervised Sequential Sensor Acquisition. | Manjesh Kumar Hanawal, Csaba Szepesvri, Venkatesh Saligrama |
| 2017 | ICML | Connected Subgraph Detection with Mirror Descent on SDPs. | Cem Aksoylar, Lorenzo Orecchia, Venkatesh Saligrama |
| 2017 | ICML | Adaptive Neural Networks for Efficient Inference. | Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama |
| 2016 | CVPR | Efficient Training of Very Deep Neural Networks for Supervised Hashing. | Ziming Zhang, Yuting Chen, Venkatesh Saligrama |
| 2016 | CVPR | Zero-Shot Learning via Joint Latent Similarity Embedding. | Ziming Zhang, Venkatesh Saligrama |
| 2016 | ECCV | Zero-Shot Recognition via Structured Prediction. | Ziming Zhang, Venkatesh Saligrama |
| 2016 | ICASSP | Efficient algorithms for linear polyhedral bandits. | Manjesh Kumar Hanawal, Amir Leshem, Venkatesh Saligrama |
| 2016 | ISLPED | Energy-Efficient Adaptive Classifier Design for Mobile Systems. | Zafar Takhirov, Joseph Wang, Venkatesh Saligrama, Ajay Joshi |
| 2015 | AISTATS | A Topic Modeling Approach to Ranking. | Weicong Ding, Prakash Ishwar, Venkatesh Saligrama |
| 2015 | AISTATS | Learning Efficient Anomaly Detectors from K-NN Graphs. | Jonathan Root, Jing Qian, Venkatesh Saligrama |
| 2015 | ICASSP | Learning shared rankings from mixtures of noisy pairwise comparisons. | Weicong Ding, Prakash Ishwar, Venkatesh Saligrama |
| 2015 | ICASSP | Efficient detection and localization on graph structured data. | Manjesh Kumar Hanawal, Venkatesh Saligrama |
| 2015 | ICASSP | Rapid: Rapidly accelerated proximal gradient algorithms for convex minimization. | Ziming Zhang, Venkatesh Saligrama |
| 2015 | ICCV | Group Membership Prediction. | Ziming Zhang, Yuting Chen, Venkatesh Saligrama |
| 2015 | ICCV | Zero-Shot Learning via Semantic Similarity Embedding. | Ziming Zhang, Venkatesh Saligrama |
| 2015 | ICML | Cheap Bandits. | Manjesh Kumar Hanawal, Venkatesh Saligrama, Michal Valko, Rmi Munos |
| 2015 | ICML | Feature-Budgeted Random Forest. | Feng Nan, Joseph Wang, Venkatesh Saligrama |
| 2015 | ISIT | Learning immune-defectives graph through group tests. | Abhinav Ganesan, Sidharth Jaggi, Venkatesh Saligrama |
| 2015 | ITA | Most large topic models are approximately separable. | Weicong Ding, Prakash Ishwar, Venkatesh Saligrama |
| 2015 | ITW | Non-adaptive group testing with inhibitors. | Abhinav Ganesan, Sidharth Jaggi, Venkatesh Saligrama |
| 2014 | AISTATS | Information-Theoretic Characterization of Sparse Recovery. | Cem Aksoylar, Venkatesh Saligrama |
| 2014 | AISTATS | Efficient Distributed Topic Modeling with Provable Guarantees. | Weicong Ding, Mohammad H. Rohban, Prakash Ishwar, Venkatesh Saligrama |
| 2014 | AISTATS | Connected Sub-graph Detection. | Jing Qian, Venkatesh Saligrama, Yuting Chen |
| 2014 | AISTATS | An LP for Sequential Learning Under Budgets. | Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama |
| 2014 | ECCV | Model Selection by Linear Programming. | Joseph Wang, Tolga Bolukbasi, Kirill Trapeznikov, Venkatesh Saligrama |
| 2014 | ECCV | A Novel Visual Word Co-occurrence Model for Person Re-identification. | Ziming Zhang, Yuting Chen, Venkatesh Saligrama |
| 2014 | ICASSP | Sensing-aware kernel SVM. | Weicong Ding, Prakash Ishwar, Venkatesh Saligrama, W. Clem Karl |
| 2014 | ICASSP | Sparse signal recovery under poisson statistics for online marketing applications. | Delaram Motamedvaziri, Mohammad Hossein Rohban, Venkatesh Saligrama |
| 2014 | ICASSP | Fast margin-based cost-sensitive classification. | Feng Nan, Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama |
| 2014 | ICASSP | Spectral clustering with imbalanced data. | Jing Qian, Venkatesh Saligrama |
| 2014 | ICASSP | Anomalous cluster detection. | Jing Qian, Venkatesh Saligrama, Yuting Chen |
| 2014 | ISIT | Information-theoretic bounds for adaptive sparse recovery. | Cem Aksoylar, Venkatesh Saligrama |
| 2013 | ACML | Locally-Linear Learning Machines (L3M). | Joseph Wang, Venkatesh Saligrama |
| 2013 | ACSSC | Dynamic topic discovery through sequential projections. | Weicong Ding, Prakash Ishwar, Venkatesh Saligrama |
| 2013 | AISTATS | Supervised Sequential Classification Under Budget Constraints. | Kirill Trapeznikov, Venkatesh Saligrama |
| 2013 | ICASSP | Compressive sensing bounds through a unifying framework for sparse models. | Cem Aksoylar, George K. Atia, Venkatesh Saligrama |
| 2013 | ICASSP | A new one-class SVM for anomaly detection. | Yuting Chen, Jing Qian, Venkatesh Saligrama |
| 2013 | ICASSP | A new geometric approach to latent topic modeling and discovery. | Weicong Ding, Mohammad H. Rohban, Prakash Ishwar, Venkatesh Saligrama |
| 2013 | ICML | Topic Discovery through Data Dependent and Random Projections. | Weicong Ding, Mohammad Hossein Rohban, Prakash Ishwar, Venkatesh Saligrama |
| 2013 | ITW | Sparse signal processing with linear and non-linear observations: A unified shannon theoretic approach. | Cem Aksoylar, George K. Atia, Venkatesh Saligrama |
| 2013 | ITW | Stochastic threshold group testing. | Chun Lam Chan, Sheng Cai, Mayank Bakshi, Sidharth Jaggi, Venkatesh Saligrama |
| 2013 | ITW | An impossibility result for high dimensional supervised learning. | Mohammad H. Rohban, Prakash Ishwar, Burkay Orten, William Clement Karl, Venkatesh Saligrama |
| 2012 | AVSS | Real-Time Activity Search of Surveillance Video. | Greg Castan, Venkatesh Saligrama, Andr-Louis Caron, Pierre-Marc Jodoin |
| 2012 | CVPR | Video anomaly detection based on local statistical aggregates. | Venkatesh Saligrama, Zhu Chen |
| 2012 | ISIT | Non-adaptive group testing: Explicit bounds and novel algorithms. | Chun Lam Chan, Sidharth Jaggi, Venkatesh Saligrama, Samar Agnihotri |
| 2011 | ICASSP | Sensing-aware classification with high-dimensional data. | Burkay Orten, Prakash Ishwar, W. Clem Karl, Venkatesh Saligrama, Homer H. Pien |
| 2010 | FUSION | Revision of marginal probability assessments. | Peter B. Jones, Sanjoy K. Mitter, Venkatesh Saligrama |
| 2010 | FUSION | A new algorithm for outlier rejection in particle filters. | Rohit Kumar, David A. Castan, Erhan Baki Ermis, Venkatesh Saligrama |
| 2010 | ICASSP | Sparsity penalized reconstruction framework for broadband dispersion extraction. | Shuchin Aeron, Sandip Bose, Henri-Pierre Valero, Venkatesh Saligrama |
| 2010 | ICASSP | On compressed blind de-convolution of filtered sparse processes. | Manqi Zhao, Venkatesh Saligrama |
| 2010 | ISIT | Graph-constrained group testing. | Mahdi Cheraghchi, Amin Karbasi, Soheil Mohajer, Venkatesh Saligrama |
| 2009 | CVPR | Abnormal events detection based on spatio-temporal co-occurences. | Yannick Benezeth, Pierre-Marc Jodoin, Venkatesh Saligrama, Christophe Rosenberger |
| 2008 | ACSSC | Codes to unmask spectrum violators in cognitive radio systems. | George K. Atia, Venkatesh Saligrama, Anant Sahai |
| 2008 | ICIP | Motion segmentation and abnormal behavior detection via behavior clustering. | Erhan Baki Ermis, Venkatesh Saligrama, Pierre-Marc Jodoin, Janusz Konrad |
| 2008 | ICIP | Motion detection with an unstable camera. | Pierre-Marc Jodoin, Janusz Konrad, Venkatesh Saligrama, Vincent Veilleux-Gaboury |
| 2008 | ICIP | Motion detection with false discovery rate control. | J. Mike McHugh, Janusz Konrad, Venkatesh Saligrama, Pierre-Marc Jodoin, David A. Castan |
| 2007 | ICASSP | Robust Distributed Detection with Limited Range Sensors. | Erhan Baki Ermis, Venkatesh Saligrama |
| 2006 | CISS | Distributed Target tracking and localization in multi-hop networks. | Shuchin Aeron, Venkatesh Saligrama, David Castanon |
| 2006 | CISS | Detection and Localization in Sensor Networks Using Distributed FDR. | Erhan Baki Ermis, Venkatesh Saligrama |
| 2006 | CISS | Randomized Sequential Algorithms for Data Aggregation in Sensor Networks. | Onur Savas, Murat Alanyali, Venkatesh Saligrama |
| 2006 | DCOSS | Efficient In-Network Processing Through Local Ad-Hoc Information Coalescence. | Onur Savas, Murat Alanyali, Venkatesh Saligrama |
| 2006 | GLOBECOM | Effect of Geometry on the Diversity-Multiplexing Tradeoff in Relay Channels. | George K. Atia, Masoud Sharif, Venkatesh Saligrama |
| 2006 | ICASSP | Reliable Tracking With Intermittent Communications. | Venkatesh Saligrama, David A. Castan |
| 2006 | WiOpt | On the macroscopic effects of local interactions in multi-hop wireless networks. | Venkatesh Saligrama, David Starobinski |
| 2005 | ICASSP | Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena. | Erhan Baki Ermis, Venkatesh Saligrama |
| 2004 | ICASSP | Performance guarantees in sensor networks. | Venkatesh Saligrama, Yonggang Shi, William Clement Karl |
| 2004 | ISIT | Capacity scaling in wireless ad-hoc networks with P | Shuchin Aeron, Venkatesh Saligrama |
| 2004 | ISIT | Classification in sensor networks. | Venkatesh Saligrama, Murat Alanyali, Onur Savas, Shuchin Aeron |