default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDVenkatesh Saligrama
Person information
- affiliation: Department of Electrical and Computer Engineering, Boston University
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j42]Samarth Mishra
, Pengkai Zhu, Venkatesh Saligrama:
Interpretable Compositional Representations for Robust Few-Shot Generalization. IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1496-1512 (2024)- [c162]Aditya Gangrade, Tianrui Chen, Venkatesh Saligrama:
Safe Linear Bandits over Unknown Polytopes. COLT 2024: 1755-1795 - [c161]Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama, Clayton Scott:
Testing the Feasibility of Linear Programs with Bandit Feedback. ICML 2024 - [i101]Samarth Mishra, Kate Saenko, Venkatesh Saligrama:
SynCDR : Training Cross Domain Retrieval Models with Synthetic Data. CoRR abs/2401.00420 (2024) - [i100]Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama, Clayton Scott:
Testing the Feasibility of Linear Programs with Bandit Feedback. CoRR abs/2406.15648 (2024) - [i99]Ruizhao Zhu, Venkatesh Saligrama:
Deep Companion Learning: Enhancing Generalization Through Historical Consistency. CoRR abs/2407.18821 (2024) - 2023
- [c160]Chen Chen, Dylan Walker, Venkatesh Saligrama:
Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the "What" and Focus on the "How"! ACL (1) 2023: 9529-9549 - [c159]Ruizhao Zhu, Pengkai Zhu, Samarth Mishra, Venkatesh Saligrama:
Fine-grained Few-shot Recognition by Deep Object Parsing. BMVC 2023: 330-331 - [c158]Ruizhao Zhu, Peng Huang, Eshed Ohn-Bar, Venkatesh Saligrama:
Learning to Drive Anywhere. CoRL 2023: 3631-3653 - [c157]Anil Kag, Durmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama:
Scaffolding a Student to Instill Knowledge. ICLR 2023 - [c156]Anil Kag, Igor Fedorov, Aditya Gangrade, Paul N. Whatmough, Venkatesh Saligrama:
Efficient Edge Inference by Selective Query. ICLR 2023 - [c155]Fangzhou Lin, Yun Yue, Ziming Zhang, Songlin Hou, Kazunori D. Yamada, Vijaya Kolachalama, Venkatesh Saligrama:
InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion. NeurIPS 2023 - [c154]Howard Zhong, Samarth Mishra, Donghyun Kim, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Aude Oliva, Rogério Feris:
Learning Human Action Recognition Representations Without Real Humans. NeurIPS 2023 - [i98]Chen Chen, Dylan Walker, Venkatesh Saligrama:
Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction. CoRR abs/2302.00239 (2023) - [i97]Ruizhao Zhu, Peng Huang, Eshed Ohn-Bar, Venkatesh Saligrama:
Learning to Drive Anywhere. CoRR abs/2309.12295 (2023) - [i96]Howard Zhong, Samarth Mishra, Donghyun Kim, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Aude Oliva, Rogério Feris:
Learning Human Action Recognition Representations Without Real Humans. CoRR abs/2311.06231 (2023) - 2022
- [c153]Anil Kag, Venkatesh Saligrama:
Condensing CNNs with Partial Differential Equations. CVPR 2022: 600-609 - [c152]Samarth Mishra, Rameswar Panda, Cheng Perng Phoo, Chun-Fu Richard Chen, Leonid Karlinsky, Kate Saenko, Venkatesh Saligrama, Rogério Schmidt Feris:
Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data. CVPR 2022: 9184-9194 - [c151]Tianrui Chen, Aditya Gangrade, Venkatesh Saligrama:
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. ICML 2022: 3123-3148 - [c150]Bhuvesh Kumar, Jacob D. Abernethy, Venkatesh Saligrama:
ActiveHedge: Hedge meets Active Learning. ICML 2022: 11694-11709 - [c149]Ali Siahkamari, Durmus Alp Emre Acar, Christopher Liao, Kelly L. Geyer, Venkatesh Saligrama, Brian Kulis:
Faster Algorithms for Learning Convex Functions. ICML 2022: 20176-20194 - [c148]Yo-whan Kim, Samarth Mishra, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Kate Saenko, Aude Oliva, Rogério Feris:
How Transferable are Video Representations Based on Synthetic Data? NeurIPS 2022 - [i95]Tianrui Chen, Aditya Gangrade, Venkatesh Saligrama:
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. CoRR abs/2204.00706 (2022) - [i94]Samarth Mishra, Pengkai Zhu, Venkatesh Saligrama:
Learning Compositional Representations for Effective Low-Shot Generalization. CoRR abs/2204.08090 (2022) - [i93]Durmus Alp Emre Acar, Venkatesh Saligrama:
FedHeN: Federated Learning in Heterogeneous Networks. CoRR abs/2207.03031 (2022) - [i92]Pengkai Zhu, Ruizhao Zhu, Samarth Mishra, Venkatesh Saligrama:
Fine-grained Few-shot Recognition by Deep Object Parsing. CoRR abs/2207.07110 (2022) - [i91]Tianrui Chen, Aditya Gangrade, Venkatesh Saligrama:
A Doubly Optimistic Strategy for Safe Linear Bandits. CoRR abs/2209.13694 (2022) - 2021
- [c147]Aditya Gangrade, Anil Kag, Venkatesh Saligrama:
Selective Classification via One-Sided Prediction. AISTATS 2021: 2179-2187 - [c146]Samarth Mishra, Kate Saenko, Venkatesh Saligrama:
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. BMVC 2021: 177 - [c145]Samarth Mishra, Zhongping Zhang, Yuan Shen, Ranjitha Kumar, Venkatesh Saligrama, Bryan A. Plummer:
Effectively Leveraging Attributes for Visual Similarity. CVPR Workshops 2021: 3904-3909 - [c144]Anil Kag, Venkatesh Saligrama:
Time Adaptive Recurrent Neural Network. CVPR 2021: 15149-15158 - [c143]Samarth Mishra, Zhongping Zhang, Yuan Shen, Ranjitha Kumar, Venkatesh Saligrama, Bryan A. Plummer:
Effectively Leveraging Attributes for Visual Similarity. ICCV 2021: 995-1004 - [c142]Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama:
Federated Learning Based on Dynamic Regularization. ICLR 2021 - [c141]Durmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama:
Debiasing Model Updates for Improving Personalized Federated Training. ICML 2021: 21-31 - [c140]Durmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama:
Memory Efficient Online Meta Learning. ICML 2021: 32-42 - [c139]Anil Kag, Venkatesh Saligrama:
Training Recurrent Neural Networks via Forward Propagation Through Time. ICML 2021: 5189-5200 - [c138]Aditya Gangrade, Anil Kag, Ashok Cutkosky, Venkatesh Saligrama:
Online Selective Classification with Limited Feedback. NeurIPS 2021: 14529-14541 - [c137]Aditya Gopalan, Braghadeesh Lakshminarayanan, Venkatesh Saligrama:
Bandit Quickest Changepoint Detection. NeurIPS 2021: 29064-29073 - [i90]Samarth Mishra, Kate Saenko, Venkatesh Saligrama:
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. CoRR abs/2101.12727 (2021) - [i89]Samarth Mishra, Zhongping Zhang, Yuan Shen, Ranjitha Kumar, Venkatesh Saligrama, Bryan A. Plummer:
Effectively Leveraging Attributes for Visual Similarity. CoRR abs/2105.01695 (2021) - [i88]Aditya Gopalan, Venkatesh Saligrama, Braghadeesh Lakshminarayanan:
Bandit Quickest Changepoint Detection. CoRR abs/2107.10492 (2021) - [i87]Aditya Gangrade, Anil Kag, Ashok Cutkosky, Venkatesh Saligrama:
Online Selective Classification with Limited Feedback. CoRR abs/2110.14243 (2021) - [i86]Ali Siahkamari, Durmus Alp Emre Acar, Christopher Liao, Kelly Geyer, Venkatesh Saligrama, Brian Kulis:
Faster Convex Lipschitz Regression via 2-block ADMM. CoRR abs/2111.01348 (2021) - [i85]Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama:
Federated Learning Based on Dynamic Regularization. CoRR abs/2111.04263 (2021) - [i84]Samarth Mishra, Rameswar Panda, Cheng Perng Phoo, Chun-Fu Chen, Leonid Karlinsky, Kate Saenko, Venkatesh Saligrama, Rogério Schmidt Feris:
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data. CoRR abs/2112.00054 (2021) - 2020
- [j41]Yao Ma, Alex Olshevsky, Csaba Szepesvári, Venkatesh Saligrama:
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. J. Mach. Learn. Res. 21: 133:1-133:36 (2020) - [j40]Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama:
Zero Shot Detection. IEEE Trans. Circuits Syst. Video Technol. 30(4): 998-1010 (2020) - [c136]Venkatesh Saligrama, Alexander Olshevsky, Julien M. Hendrickx:
Minimax Rank-$1$ Matrix Factorization. AISTATS 2020: 3426-3436 - [c135]Durmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama:
Budget Learning via Bracketing. AISTATS 2020: 4109-4119 - [c134]Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama:
Don't Even Look Once: Synthesizing Features for Zero-Shot Detection. CVPR 2020: 11690-11699 - [c133]Anil Kag, Ziming Zhang, Venkatesh Saligrama:
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? ICLR 2020 - [c132]Julien M. Hendrickx, Alex Olshevsky, Venkatesh Saligrama:
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model. ICML 2020: 4193-4202 - [c131]Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama:
Piecewise Linear Regression via a Difference of Convex Functions. ICML 2020: 8895-8904 - [c130]Pengkai Zhu, Ruizhao Zhu, Samarth Mishra, Venkatesh Saligrama:
Low Dimensional Visual Attributes: An Interpretable Image Encoding. ICPR Workshops (3) 2020: 90-102 - [c129]Yun Yue, Ming Li, Venkatesh Saligrama, Ziming Zhang:
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. ICPR 2020: 10532-10539 - [c128]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Limits on Testing Structural Changes in Ising Models. NeurIPS 2020 - [c127]Ali Siahkamari, Xide Xia, Venkatesh Saligrama, David A. Castañón, Brian Kulis:
Learning to Approximate a Bregman Divergence. NeurIPS 2020 - [c126]Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama:
Online Algorithm for Unsupervised Sequential Selection with Contextual Information. NeurIPS 2020 - [i83]Aditya Gangrade, Durmus Alp Emre Acar, Venkatesh Saligrama:
Budget Learning via Bracketing. CoRR abs/2004.06298 (2020) - [i82]Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama:
Piecewise Linear Regression via a Difference of Convex Functions. CoRR abs/2007.02422 (2020) - [i81]Yun Yue, Ming Li, Venkatesh Saligrama, Ziming Zhang:
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. CoRR abs/2010.05397 (2020) - [i80]Aditya Gangrade, Anil Kag, Venkatesh Saligrama:
Selective Classification via One-Sided Prediction. CoRR abs/2010.07853 (2020) - [i79]Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama:
Online Algorithm for Unsupervised Sequential Selection with Contextual Information. CoRR abs/2010.12353 (2020) - [i78]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Limits on Testing Structural Changes in Ising Models. CoRR abs/2011.03678 (2020)
2010 – 2019
- 2019
- [j39]Yuting Chen, Joseph Wang, Yannan Bai, Gregory D. Castañón, Venkatesh Saligrama:
Probabilistic Semantic Retrieval for Surveillance Videos With Activity Graphs. IEEE Trans. Multim. 21(3): 704-716 (2019) - [c125]Pengkai Zhu, Durmus Alp Emre Acar, Nan Feng, Prateek Jain, Venkatesh Saligrama:
Cost aware Inference for IoT Devices. AISTATS 2019: 2770-2779 - [c124]Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama:
Online Algorithm for Unsupervised Sensor Selection. AISTATS 2019: 3168-3176 - [c123]Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama:
Generalized Zero-Shot Recognition Based on Visually Semantic Embedding. CVPR 2019: 2995-3003 - [c122]Md. Rizwan Parvez, Tolga Bolukbasi, Kai-Wei Chang, Venkatesh Saligrama:
Robust Text Classifier on Test-Time Budgets. EMNLP/IJCNLP (1) 2019: 1167-1172 - [c121]Hanxiao Wang, Venkatesh Saligrama, Stan Sclaroff, Vitaly Ablavsky:
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations. ICCV 2019: 1252-1261 - [c120]Julien M. Hendrickx, Alexander Olshevsky, Venkatesh Saligrama:
Graph Resistance and Learning from Pairwise Comparisons. ICML 2019: 2702-2711 - [c119]Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama:
Learning Classifiers for Target Domain with Limited or No Labels. ICML 2019: 7643-7653 - [c118]Aditya Gangrade, Praveen Venkatesh, Bobak Nazer, Venkatesh Saligrama:
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models. NeurIPS 2019: 10364-10375 - [c117]Don Kurian Dennis, Durmus Alp Emre Acar, Vikram Mandikal, Vinu Sankar Sadasivan, Venkatesh Saligrama, Harsha Vardhan Simhadri, Prateek Jain:
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices. NeurIPS 2019: 12896-12906 - [i77]Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama:
Online Algorithm for Unsupervised Sensor Selection. CoRR abs/1901.04676 (2019) - [i76]Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama:
Learning for New Visual Environments with Limited Labels. CoRR abs/1901.09079 (2019) - [i75]Julien M. Hendrickx, Alex Olshevsky, Venkatesh Saligrama:
Graph Resistance and Learning from Pairwise Comparisons. CoRR abs/1902.00141 (2019) - [i74]Ziming Zhang, Anil Kag, Alan Sullivan, Venkatesh Saligrama:
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability. CoRR abs/1903.00755 (2019) - [i73]Yao Ma, Alex Olshevsky, Venkatesh Saligrama, Csaba Szepesvári:
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. CoRR abs/1904.11608 (2019) - [i72]Ali Siahkamari, Venkatesh Saligrama, David Castanon, Brian Kulis:
Learning Bregman Divergences. CoRR abs/1905.11545 (2019) - [i71]Anil Kag, Ziming Zhang, Venkatesh Saligrama:
RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? CoRR abs/1908.08574 (2019) - [i70]Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama:
Dont Even Look Once: Synthesizing Features for Zero-Shot Detection. CoRR abs/1911.07933 (2019) - 2018
- [j38]Ziming Zhang, Yun Liu, Xi Chen, Yanjun Zhu, Ming-Ming Cheng, Venkatesh Saligrama, Philip H. S. Torr:
Sequential Optimization for Efficient High-Quality Object Proposal Generation. IEEE Trans. Pattern Anal. Mach. Intell. 40(5): 1209-1223 (2018) - [j37]Anelia Somekh-Baruch, Amir Leshem, Venkatesh Saligrama:
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems. IEEE Trans. Inf. Theory 64(8): 5549-5554 (2018) - [c116]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds. ICASSP 2018: 6931-6935 - [c115]Yao Ma, Alexander Olshevsky, Csaba Szepesvári, Venkatesh Saligrama:
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. ICML 2018: 3341-3350 - [i69]Pengkai Zhu, Hanxiao Wang, Tolga Bolukbasi, Venkatesh Saligrama:
Zero-Shot Detection. CoRR abs/1803.07113 (2018) - [i68]Hanxiao Wang, Venkatesh Saligrama, Stan Sclaroff, Vitaly Ablavsky:
Learning Where to Fixate on Foveated Images. CoRR abs/1811.06868 (2018) - [i67]Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama:
Generalized Zero-Shot Recognition based on Visually Semantic Embedding. CoRR abs/1811.07993 (2018) - [i66]Aditya Gangrade, Praveen Venkatesh, Bobak Nazer, Venkatesh Saligrama:
Testing Changes in Communities for the Stochastic Block Model. CoRR abs/1812.00769 (2018) - 2017
- [j36]Ziming Zhang, Venkatesh Saligrama:
PRISM: Person Reidentification via Structured Matching. IEEE Trans. Circuits Syst. Video Technol. 27(3): 499-512 (2017) - [j35]Cem Aksoylar, George K. Atia, Venkatesh Saligrama:
Sparse Signal Processing With Linear and Nonlinear Observations: A Unified Shannon-Theoretic Approach. IEEE Trans. Inf. Theory 63(2): 749-776 (2017) - [j34]Abhinav Ganesan, Sidharth Jaggi, Venkatesh Saligrama:
Learning Immune-Defectives Graph Through Group Tests. IEEE Trans. Inf. Theory 63(5): 3010-3028 (2017) - [j33]Feng Nan, Venkatesh Saligrama:
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". IEEE Trans. Inf. Theory 63(11): 7612-7614 (2017) - [j32]Cem Aksoylar, Jing Qian, Venkatesh Saligrama:
Clustering and Community Detection With Imbalanced Clusters. IEEE Trans. Signal Inf. Process. over Networks 3(1): 61-76 (2017) - [c114]Tolga Bolukbasi, Kai-Wei Chang, Joseph Wang, Venkatesh Saligrama:
Resource Constrained Structured Prediction. AAAI 2017: 1756-1762 - [c113]Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama:
Unsupervised Sequential Sensor Acquisition. AISTATS 2017: 803-811 - [c112]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Lower bounds for two-sample structural change detection in ising and Gaussian models. Allerton 2017: 1016-1025 - [c111]Cem Aksoylar, Lorenzo Orecchia, Venkatesh Saligrama:
Connected Subgraph Detection with Mirror Descent on SDPs. ICML 2017: 51-59 - [c110]Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama:
Adaptive Neural Networks for Efficient Inference. ICML 2017: 527-536 - [c109]Feng Nan, Venkatesh Saligrama:
Adaptive Classification for Prediction Under a Budget. NIPS 2017: 4727-4737 - [i65]Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama:
Adaptive Neural Networks for Fast Test-Time Prediction. CoRR abs/1702.07811 (2017) - [i64]Zafar Takhirov, Joseph Wang, Marcia S. Louis, Venkatesh Saligrama, Ajay Joshi:
Field of Groves: An Energy-Efficient Random Forest. CoRR abs/1704.02978 (2017) - [i63]Feng Nan, Venkatesh Saligrama:
Dynamic Model Selection for Prediction Under a Budget. CoRR abs/1704.07505 (2017) - [i62]Feng Nan, Venkatesh Saligrama:
Comments on the proof of adaptive submodular function minimization. CoRR abs/1705.03771 (2017) - [i61]Feng Nan, Venkatesh Saligrama:
Adaptive Classification for Prediction Under a Budget. CoRR abs/1705.10194 (2017) - [i60]Henghui Zhu, Feng Nan, Ioannis Ch. Paschalidis, Venkatesh Saligrama:
Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget. CoRR abs/1705.10924 (2017) - [i59]Yao Ma, Alex Olshevsky, Venkatesh Saligrama, Csaba Szepesvári:
Crowdsourcing with Sparsely Interacting Workers. CoRR abs/1706.06660 (2017) - [i58]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Lower Bounds for Two-Sample Structural Change Detection in Ising and Gaussian Models. CoRR abs/1710.10366 (2017) - [i57]Yuting Chen, Joseph Wang, Yannan Bai, Gregory D. Castañón, Venkatesh Saligrama:
Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs. CoRR abs/1712.06204 (2017) - 2016
- [j31]Weicong Ding, Prakash Ishwar, Venkatesh Saligrama:
A Provably Efficient Algorithm for Separable Topic Discovery. IEEE J. Sel. Top. Signal Process. 10(4): 712-725 (2016) - [j30]Greg Castañón, Mohamed A. Elgharib, Venkatesh Saligrama, Pierre-Marc Jodoin:
Retrieval in Long-Surveillance Videos Using User-Described Motion and Object Attributes. IEEE Trans. Circuits Syst. Video Technol. 26(12): 2313-2327 (2016) - [j29]Vincenzo Matta, Cédric Richard, Venkatesh Saligrama, Ali H. Sayed:
Guest Editorial Inference and Learning over Networks. IEEE Trans. Signal Inf. Process. over Networks 2(4): 423-425 (2016) - [j28]Mohammad Hossein Rohban, Venkatesh Saligrama, Delaram Motamed Vaziri:
Minimax Optimal Sparse Signal Recovery With Poisson Statistics. IEEE Trans. Signal Process. 64(13): 3495-3508 (2016) - [c108]Huanyu Ding, Eric Cristofalo, Joseph Wang, David A. Castañón, Eduardo Montijano, Venkatesh Saligrama, Mac Schwager:
A multi-resolution approach for discovery and 3-D modeling of archaeological sites using satellite imagery and a UAV-borne camera. ACC 2016: 1359-1365 - [c107]Ziming Zhang, Yuting Chen, Venkatesh Saligrama:
Efficient Training of Very Deep Neural Networks for Supervised Hashing. CVPR 2016: 1487-1495 - [c106]Ziming Zhang, Venkatesh Saligrama:
Zero-Shot Learning via Joint Latent Similarity Embedding. CVPR 2016: 6034-6042 - [c105]Ziming Zhang, Venkatesh Saligrama:
Zero-Shot Recognition via Structured Prediction. ECCV (7) 2016: 533-548 - [c104]Manjesh Kumar Hanawal, Amir Leshem, Venkatesh Saligrama:
Efficient algorithms for linear polyhedral bandits. ICASSP 2016: 4796-4800 - [c103]Zafar Takhirov, Joseph Wang, Venkatesh Saligrama, Ajay Joshi:
Energy-Efficient Adaptive Classifier Design for Mobile Systems. ISLPED 2016: 52-57 - [c102]Feng Nan, Joseph Wang, Venkatesh Saligrama:
Pruning Random Forests for Prediction on a Budget. NIPS 2016: 2334-2342 - [c101]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai:
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. NIPS 2016: 4349-4357 - [i56]Feng Nan, Joseph Wang, Venkatesh Saligrama:
Optimally Pruning Decision Tree Ensembles With Feature Cost. CoRR abs/1601.00955 (2016) - [i55]Jonathan Root, Venkatesh Saligrama, Jing Qian:
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs. CoRR abs/1601.06105 (2016) - [i54]Tolga Bolukbasi, Kai-Wei Chang, Joseph Wang, Venkatesh Saligrama:
Structured Prediction with Test-time Budget Constraints. CoRR abs/1602.08761 (2016) - [i53]