Sanjiv Kumar - RankMe

266 papers A* 91A 8C 1Misc 1Journal 142Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Review of Prognosis Approaches Applied to Power SiC MOSFETs for Health State and Remaining Useful Life Prediction. Entropy Sanjiv Kumar, Bruno Allard, Malorie Hologne, Guy Clerc, François Auger
2025	J	`jnl`	Analyzing Similarity Metrics for Data Selection for Language Model Pretraining. CoRR Dylan Sam, Ayan Chakrabarti, Afshin Rostamizadeh, Srikumar Ramalingam, Gui Citovsky, Sanjiv Kumar
2025	A*	`conf`	Better autoregressive regression with LLMs via regression-aware fine-tuning. ICLR Michal Lukasik, Zhao Meng, Harikrishna Narasimhan, Yin-Wen Chang, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar
2025	A*	`conf`	Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation. ICML Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, MohammadHossein Bateni, Sanjiv Kumar
2025	J	`jnl`	Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation. CoRR Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, MohammadHossein Bateni, Sanjiv Kumar
2025	J	`jnl`	Deep sequence models tend to memorize geometrically; it is unclear why. CoRR Shahriar Noroozizadeh, Vaishnavh Nagarajan, Elan Rosenfeld, Sanjiv Kumar
2025	A*	`conf`	Efficient stagewise pretraining via progressive subnetworks. ICLR Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar
2025	A*	`conf`	Faster Cascades via Speculative Decoding. ICLR Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar
2025	J	`jnl`	Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe. CoRR Chong You, Rajesh Jayaram, Ananda Theertha Suresh, Robin Nittka, Felix X. Yu, Sanjiv Kumar
2025	A*	`conf`	LAuReL: Learned Augmented Residual Layer. ICML Gaurav Menghani, Ravi Kumar, Sanjiv Kumar
2025	A*	`conf`	LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. ICLR Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar
2025	A*	`conf`	Reasoning with Latent Thoughts: On the Power of Looped Transformers. ICLR Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, Sanjiv Kumar, Sashank J. Reddi
2025	J	`jnl`	Reasoning with Latent Thoughts: On the Power of Looped Transformers. CoRR Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, Sanjiv Kumar, Sashank J. Reddi
2025	J	`jnl`	Scalable In-context Ranking with Generative Models. CoRR Nilesh Gupta, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Inderjit S. Dhillon, Felix X. Yu
2025	J	`jnl`	Spark Transformer: Reactivating Sparsity in FFN and Attention. CoRR Chong You, Kan Wu, Zhipeng Jia, Lin Chen, Srinadh Bhojanapalli, Jiaxian Guo, Utku Evci, Jan Wassenberg, Praneeth Netrapalli, Jeremiah J. Willcock, Suvinay Subramanian, Felix Chern, Alek Andreev, Shreya Pathak, Felix X. Yu, Prateek Jain, David E. Culler, Henry M. Levy, Sanjiv Kumar
2025	A*	`conf`	Structured Preconditioners in Adaptive Optimization: A Unified Analysis. ICML Shuo Xie, Tianhao Wang, Sashank J. Reddi, Sanjiv Kumar, Zhiyuan Li
2025	J	`jnl`	Structured Preconditioners in Adaptive Optimization: A Unified Analysis. CoRR Shuo Xie, Tianhao Wang, Sashank Reddi, Sanjiv Kumar, Zhiyuan Li
2025	J	`jnl`	Universal Model Routing for Efficient LLM Inference. CoRR Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Jeevesh Juneja, Zifeng Wang, Chen-Yu Lee, Pradeep Shenoy, Rina Panigrahy, Aditya Krishna Menon, Sanjiv Kumar
2024	J	`jnl`	A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs. CoRR Ankit Singh Rawat, Veeranjaneyulu Sadhanala, Afshin Rostamizadeh, Ayan Chakrabarti, Wittawat Jitkrittum, Vladimir Feinberg, Seungyeon Kim, Hrayr Harutyunyan, Nikunj Saunshi, Zachary Nado, Rakesh Shivanna, Sashank J. Reddi, Aditya Krishna Menon, Rohan Anil, Sanjiv Kumar
2024	A*	`conf`	Accelerating Blockwise Parallel Language Models with Draft Refinement. NeurIPS Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael D. Riley, Sanjiv Kumar, Adrian Benton
2024	A*	`conf`	Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning? ICML Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar
2024	J	`jnl`	Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning? CoRR Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar
2024	A*	`conf`	DistillSpec: Improving Speculative Decoding via Knowledge Distillation. ICLR Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal
2024	J	`jnl`	Efficient Document Ranking with Learnable Late Interactions. CoRR Ziwei Ji, Himanshu Jain, Andreas Veit, Sashank J. Reddi, Sadeep Jayasumana, Ankit Singh Rawat, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar
2024	J	`jnl`	Efficient Stagewise Pretraining via Progressive Subnetworks. CoRR Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar
2024	J	`jnl`	Faster Cascades via Speculative Decoding. CoRR Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar
2024	A*	`conf`	Functional Interpolation for Relative Positions improves Long Context Transformers. ICLR Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
2024	J	`jnl`	HiRE: High Recall Approximate Top-k Estimation for Efficient LLM Inference. CoRR Yashas Samaga, Varun Yerram, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli
2024	J	`jnl`	LAuReL: Learned Augmented Residual Layer. CoRR Gaurav Menghani, Ravi Kumar, Sanjiv Kumar
2024	J	`jnl`	Landscape-Aware Growing: The Power of a Little LAG. CoRR Stefani Karp, Nikunj Saunshi, Sobhan Miryoosefi, Sashank J. Reddi, Sanjiv Kumar
2024	A*	`conf`	Language Model Cascades: Token-Level Uncertainty And Beyond. ICLR Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2024	J	`jnl`	Language Model Cascades: Token-level uncertainty and beyond. CoRR Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2024	J	`jnl`	LatentCRF: Continuous CRF for Efficient Latent Diffusion. CoRR Kanchana Ranasinghe, Sadeep Jayasumana, Andreas Veit, Ayan Chakrabarti, Daniel Glasner, Michael S. Ryoo, Srikumar Ramalingam, Sanjiv Kumar
2024	A*	`conf`	Learning to Reject Meets Long-tail Learning. ICLR Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar
2024	J	`jnl`	LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. CoRR Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar
2024	A*	`conf`	MarkovGen: Structured Prediction for Efficient Text-to-Image Generation. CVPR Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar
2024	J	`jnl`	Metric-aware LLM inference. CoRR Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar
2024	J	`jnl`	Mimetic Initialization Helps State Space Models Learn to Recall. CoRR Asher Trockman, Hrayr Harutyunyan, J. Zico Kolter, Sanjiv Kumar, Srinadh Bhojanapalli
2024	J	`jnl`	No more hard prompts: SoftSRV prompting for synthetic data generation. CoRR Giulia DeSalvo, Jean-François Kagy, Lazaros Karydas, Afshin Rostamizadeh, Sanjiv Kumar
2024	A*	`conf`	On Bias-Variance Alignment in Deep Models. ICLR Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar
2024	A*	`conf`	On the Inductive Bias of Stacking Towards Improving Reasoning. NeurIPS Nikunj Saunshi, Stefani Karp, Shankar Krishnan, Sobhan Miryoosefi, Sashank Jakkam Reddi, Sanjiv Kumar
2024	J	`jnl`	On the Inductive Bias of Stacking Towards Improving Reasoning. CoRR Nikunj Saunshi, Stefani Karp, Shankar Krishnan, Sobhan Miryoosefi, Sashank J. Reddi, Sanjiv Kumar
2024	J	`jnl`	On the Role of Depth and Looping for In-Context Learning with Task Diversity. CoRR Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar
2024	A*	`conf`	Plugin estimators for selective classification with out-of-distribution detection. ICLR Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
2024	A*	`conf`	Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines. ICML Yuchen Li, Alexandre Kirchmeyer, Aashay Mehta, Yilong Qin, Boris Dadachev, Kishore Papineni, Sanjiv Kumar, Andrej Risteski
2024	J	`jnl`	Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines. CoRR Yuchen Li, Alexandre Kirchmeyer, Aashay Mehta, Yilong Qin, Boris Dadachev, Kishore Papineni, Sanjiv Kumar, Andrej Risteski
2024	—	`conf`	Regression Aware Inference with LLMs. EMNLP (Findings) Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar
2024	A*	`conf`	Rethinking FID: Towards a Better Evaluation Metric for Image Generation. CVPR Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar
2024	J	`jnl`	Rethinking FID: Towards a Better Evaluation Metric for Image Generation. CoRR Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar
2024	J	`jnl`	SOAR: Improved Indexing for Approximate Nearest Neighbor Search. CoRR Philip Sun, David Simcha, Dave Dopson, Ruiqi Guo, Sanjiv Kumar
2024	J	`jnl`	SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection. CoRR Ke Ye, Heinrich Jiang, Afshin Rostamizadeh, Ayan Chakrabarti, Giulia DeSalvo, Jean-François Kagy, Lazaros Karydas, Gui Citovsky, Sanjiv Kumar
2024	A*	`conf`	Tandem Transformers for Inference Efficient LLMs. ICML Aishwarya P. S., Pranav Ajit Nair, Yashas Samaga, Toby Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli
2024	J	`jnl`	Tandem Transformers for Inference Efficient LLMs. CoRR Aishwarya P. S., Pranav Ajit Nair, Yashas Samaga, Toby Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli
2024	A*	`conf`	Think before you speak: Training Language Models With Pause Tokens. ICLR Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, Vaishnavh Nagarajan
2024	J	`jnl`	Towards Fast Inference: Exploring and Improving Blockwise Parallel Drafts. CoRR Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael Riley, Sanjiv Kumar, Adrian Benton
2024	A*	`conf`	Two-stage LLM Fine-tuning with Less Specialization and More Generalization. ICLR Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
2024	A*	`conf`	USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval. ICML Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar
2024	J	`jnl`	What do larger image classifiers memorise? Trans. Mach. Learn. Res. Michal Lukasik, Vaishnavh Nagarajan, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2024	J	`jnl`	Who Gets Protected? A Fairness Analysis of Cross-Lingual Social Bias Detection for Hindi. Bull. Comput. Data Sci. Sonia Shahzadi, Sanjiv Kumar
2023	C	`conf`	A Framework for Developing the Next Generation Interactive Soil Moisture Forecasting System Using the Long-Short Term Memory Model. ICMLA Guna Shekar M., Wonjun Lee, Sanjiv Kumar, Yanan Duan, Imtiaz Rangwala
2023	J	`jnl`	A Weighted K-Center Algorithm for Data Subset Selection. CoRR Srikumar Ramalingam, Pranjal Awasthi, Sanjiv Kumar
2023	A*	`conf`	Automating Nearest Neighbor Search Configuration with Constrained Optimization. ICLR Philip Sun, Ruiqi Guo, Sanjiv Kumar
2023	J	`jnl`	Automating Nearest Neighbor Search Configuration with Constrained Optimization. CoRR Philip Sun, Ruiqi Guo, Sanjiv Kumar
2023	J	`jnl`	Depth Dependence of μP Learning Rates in ReLU MLPs. CoRR Samy Jelassi, Boris Hanin, Ziwei Ji, Sashank J. Reddi, Srinadh Bhojanapalli, Sanjiv Kumar
2023	J	`jnl`	DistillSpec: Improving Speculative Decoding via Knowledge Distillation. CoRR Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal
2023	A*	`conf`	Efficient Training of Language Models using Few-Shot Learning. ICML Sashank J. Reddi, Sobhan Miryoosefi, Stefani Karp, Shankar Krishnan, Satyen Kale, Seungyeon Kim, Sanjiv Kumar
2023	J	`jnl`	EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval. CoRR Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar
2023	J	`jnl`	Enhancing Depression Detection in Social Media via Advanced User Profiling and Fine-Grained Age Groups. Bull. Comput. Data Sci. Sonia Shahzadi, Sanjiv Kumar, Harsh Mehta
2023	J	`jnl`	Functional Interpolation for Relative Positions Improves Long Context Transformers. CoRR Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
2023	J	`jnl`	It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models. CoRR Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar
2023	—	`conf`	Large Language Models with Controllable Working Memory. ACL (Findings) Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar
2023	J	`jnl`	Learning to reject meets OOD detection: Are all abstentions created equal? CoRR Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
2023	A*	`conf`	Leveraging Importance Weights in Subset Selection. ICLR Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang
2023	J	`jnl`	Leveraging Importance Weights in Subset Selection. CoRR Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang
2023	A*	`conf`	On student-teacher deviations in distillation: does it pay to disobey? NeurIPS Vaishnavh Nagarajan, Aditya Krishna Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar
2023	J	`jnl`	On student-teacher deviations in distillation: does it pay to disobey? CoRR Vaishnavh Nagarajan, Aditya Krishna Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar
2023	J	`jnl`	ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent. CoRR Renat Aksitov, Sobhan Miryoosefi, Zonglin Li, Daliang Li, Sheila Babayan, Kavya Kopparapu, Zachary Fisher, Ruiqi Guo, Sushant Prakash, Pranesh Srinivasan, Manzil Zaheer, Felix X. Yu, Sanjiv Kumar
2023	A*	`conf`	ResMem: Learn what you can and memorize the rest. NeurIPS Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar
2023	J	`jnl`	ResMem: Learn what you can and memorize the rest. CoRR Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar
2023	A*	`conf`	SOAR: Improved Indexing for Approximate Nearest Neighbor Search. NeurIPS Philip Sun, David Simcha, Dave Dopson, Ruiqi Guo, Sanjiv Kumar
2023	J	`jnl`	SPEGTI: Structured Prediction for Efficient Generative Text-to-Image Models. CoRR Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar
2023	A*	`conf`	Serving Graph Compression for Graph Neural Networks. ICLR Si Si, Felix X. Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar
2023	A*	`conf`	Supervision Complexity and its Role in Knowledge Distillation. ICLR Hrayr Harutyunyan, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar
2023	J	`jnl`	Supervision Complexity and its Role in Knowledge Distillation. CoRR Hrayr Harutyunyan, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar
2023	A*	`conf`	Teacher Guided Training: An Efficient Framework for Knowledge Transfer. ICLR Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar
2023	A*	`conf`	The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers. ICLR Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix Chern, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar
2023	J	`jnl`	Think before you speak: Training Language Models With Pause Tokens. CoRR Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, Vaishnavh Nagarajan
2023	J	`jnl`	What do larger image classifiers memorise? CoRR Michal Lukasik, Vaishnavh Nagarajan, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2023	A*	`conf`	When Does Confidence-Based Cascade Deferral Suffice? NeurIPS Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
2023	J	`jnl`	When Does Confidence-Based Cascade Deferral Suffice? CoRR Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
2022	A*	`conf`	Decoupled Context Processing for Context Augmented Language Modeling. NeurIPS Zonglin Li, Ruiqi Guo, Sanjiv Kumar
2022	J	`jnl`	Decoupled Context Processing for Context Augmented Language Modeling. CoRR Zonglin Li, Ruiqi Guo, Sanjiv Kumar
2022	J	`jnl`	ELM: Embedding and Logit Margins for Long-Tail Learning. CoRR Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
2022	A*	`conf`	In defense of dual-encoders for neural ranking. ICML Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar
2022	J	`jnl`	Large Language Models with Controllable Working Memory. CoRR Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar
2022	J	`jnl`	Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers. CoRR Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix Chern, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar
2022	A*	`conf`	Post-hoc estimators for learning to defer to an expert. NeurIPS Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
2022	J	`jnl`	Predicting on the Edge: Identifying Where a Larger Model Does Better. CoRR Taman Narayan, Heinrich Jiang, Sen Zhao, Sanjiv Kumar
2022	J	`jnl`	Preserving In-Context Learning ability in Large Language Model Fine-tuning. CoRR Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
2022	—	`conf`	Radio over FSO System for 5G Wireless Communication. ICCCNT Gautam Gautam, Neeraj Sharma, Sanjiv Kumar
2022	A*	`conf`	Robust Training of Neural Networks Using Scale Invariant Architectures. ICML Zhiyuan Li, Srinadh Bhojanapalli, Manzil Zaheer, Sashank J. Reddi, Sanjiv Kumar
2022	J	`jnl`	Robust Training of Neural Networks using Scale Invariant Architectures. CoRR Zhiyuan Li, Srinadh Bhojanapalli, Manzil Zaheer, Sashank J. Reddi, Sanjiv Kumar
2022	A*	`conf`	TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s. NeurIPS Felix Chern, Blake Hechtman, Andy Davis, Ruiqi Guo, David Majnemer, Sanjiv Kumar
2022	J	`jnl`	TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s. CoRR Felix Chern, Blake Hechtman, Andy Davis, Ruiqi Guo, David Majnemer, Sanjiv Kumar
2022	J	`jnl`	Teacher Guided Training: An Efficient Framework for Knowledge Transfer. CoRR Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar
2022	J	`jnl`	Teacher's pet: understanding and mitigating biases in distillation. Trans. Mach. Learn. Res. Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
2022	J	`jnl`	When does mixup promote local linearity in learned representations? CoRR Arslan Chaudhry, Aditya Krishna Menon, Andreas Veit, Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar
2021	A*	`conf`	A statistical perspective on distillation. ICML Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar
2021	A*	`conf`	Adaptive Federated Optimization. ICLR Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konecný, Sanjiv Kumar, Hugh Brendan McMahan
2021	J	`jnl`	Balancing Constraints and Submodularity in Data Subset Selection. CoRR Srikumar Ramalingam, Daniel Glasner, Kaushal Patel, Raviteja Vemulapalli, Sadeep Jayasumana, Sanjiv Kumar
2021	J	`jnl`	Balancing Robustness and Sensitivity using Feature Contrastive Learning. CoRR Seungyeon Kim, Daniel Glasner, Srikumar Ramalingam, Cho-Jui Hsieh, Kishore Papineni, Sanjiv Kumar
2021	A*	`conf`	Batch Active Learning at Scale. NeurIPS Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar
2021	J	`jnl`	Batch Active Learning at Scale. CoRR Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar
2021	A*	`conf`	Coping with Label Shift via Distributionally Robust Optimisation. ICLR Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
2021	J	`jnl`	Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces. CoRR Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2021	A*	`conf`	Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces. ICML Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2021	A*	`conf`	Efficient Training of Retrieval Models using Negative Cache. NeurIPS Erik Lindgren, Sashank J. Reddi, Ruiqi Guo, Sanjiv Kumar
2021	J	`jnl`	Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation. CoRR Srinadh Bhojanapalli, Ayan Chakrabarti, Himanshu Jain, Sanjiv Kumar, Michal Lukasik, Andreas Veit
2021	A*	`conf`	Evaluations and Methods for Explanation through Robustness Analysis. ICLR Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Kumar Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
2021	J	`jnl`	Leveraging redundancy in attention with Reuse Transformers. CoRR Srinadh Bhojanapalli, Ayan Chakrabarti, Andreas Veit, Michal Lukasik, Himanshu Jain, Frederick Liu, Yin-Wen Chang, Sanjiv Kumar
2021	A*	`conf`	Long-tail learning via logit adjustment. ICLR Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
2021	J	`jnl`	On the Reproducibility of Neural Network Predictions. CoRR Srinadh Bhojanapalli, Kimberly Wilber, Andreas Veit, Ankit Singh Rawat, Seungyeon Kim, Aditya Krishna Menon, Sanjiv Kumar
2021	A*	`conf`	Overparameterisation and worst-case generalisation: friend or foe? ICLR Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
2021	A	`conf`	RankDistil: Knowledge Distillation for Ranking. AISTATS Sashank J. Reddi, Rama Kumar Pasumarthi, Aditya Krishna Menon, Ankit Singh Rawat, Felix X. Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar
2021	J	`jnl`	Routing Protocols in Delay Tolerant Networks: Comparative and Empirical Analysis. Wirel. Pers. Commun. Ankita Verma, Savita, Sanjiv Kumar
2021	J	`jnl`	Scaling Hierarchical Agglomerative Clustering to Billion-sized Datasets. CoRR Baris Sumengen, Anand Rajagopalan, Gui Citovsky, David Simcha, Olivier Bachem, Pradipta Mitra, Sam Blasiak, Mason Liang, Sanjiv Kumar
2021	J	`jnl`	Teacher's pet: understanding and mitigating biases in distillation. CoRR Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
2021	J	`jnl`	When in Doubt, Summon the Titans: Efficient Inference with Large Models. CoRR Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Amr Ahmed, Sanjiv Kumar
2020	J	`jnl`	$O(n)$ Connections are Expressive Enough: Universal Approximability of Sparse Transformers. CoRR Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	A*	`conf`	Accelerating Large-Scale Inference with Anisotropic Vector Quantization. ICML Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar
2020	J	`jnl`	Adaptive Federated Optimization. CoRR Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konecný, Sanjiv Kumar, H. Brendan McMahan
2020	A*	`conf`	Are Transformers universal approximators of sequence-to-sequence functions? ICLR Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	A*	`conf`	Can gradient clipping mitigate label noise? ICLR Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	J	`jnl`	Coping with Label Shift via Distributionally Robust Optimisation. CoRR Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
2020	A*	`conf`	Does label smoothing mitigate label noise? ICML Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
2020	J	`jnl`	Does label smoothing mitigate label noise? CoRR Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
2020	J	`jnl`	Doubly-stochastic mining for heterogeneous retrieval. CoRR Ankit Singh Rawat, Aditya Krishna Menon, Andreas Veit, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2020	J	`jnl`	Evaluations and Methods for Explanation through Robustness Analysis. CoRR Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
2020	A*	`conf`	Federated Learning with Only Positive Labels. ICML Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2020	J	`jnl`	Federated Learning with Only Positive Labels. CoRR Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2020	A*	`conf`	How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework. CVPR Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
2020	J	`jnl`	Kernelized Classification in Deep Networks. CoRR Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar
2020	A*	`conf`	Large Batch Optimization for Deep Learning: Training BERT in 76 minutes. ICLR Yang You, Jing Li, Sashank J. Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, Cho-Jui Hsieh
2020	A*	`conf`	Learning discrete distributions: user vs item-level privacy. NeurIPS Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley
2020	J	`jnl`	Learning discrete distributions: user vs item-level privacy. CoRR Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley
2020	A*	`conf`	Learning to Learn by Zeroth-Order Oracle. ICLR Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh
2020	J	`jnl`	Long-tail learning via logit adjustment. CoRR Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
2020	A*	`conf`	Low-Rank Bottleneck in Multi-head Attention Models. ICML Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	J	`jnl`	Low-Rank Bottleneck in Multi-head Attention Models. CoRR Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	J	`jnl`	Modifying Memories in Transformer Models. CoRR Chen Zhu, Ankit Singh Rawat, Manzil Zaheer, Srinadh Bhojanapalli, Daliang Li, Felix X. Yu, Sanjiv Kumar
2020	A*	`conf`	Multi-Stage Influence Function. NeurIPS Hongge Chen, Si Si, Yang Li, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh
2020	J	`jnl`	Multi-Stage Influence Function. CoRR Hongge Chen, Si Si, Yang Li, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh
2020	A*	`conf`	O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers. NeurIPS Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	A*	`conf`	Pre-training Tasks for Embedding-based Large-scale Retrieval. ICLR Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar
2020	J	`jnl`	Pre-training Tasks for Embedding-based Large-scale Retrieval. CoRR Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar
2020	J	`jnl`	Robust Large-Margin Learning in Hyperbolic Space. CoRR Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2020	A*	`conf`	Robust large-margin learning in hyperbolic space. NeurIPS Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2020	—	`conf`	Semantic Label Smoothing for Sequence to Sequence Problems. EMNLP (1) Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar
2020	J	`jnl`	Semantic Label Smoothing for Sequence to Sequence Problems. CoRR Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar
2020	A	`conf`	Tight Analysis of Privacy and Utility Tradeoff in Approximate Differential Privacy. AISTATS Quan Geng, Wei Ding, Ruiqi Guo, Sanjiv Kumar
2020	A*	`conf`	Why are Adaptive Methods Good for Attention Models? NeurIPS Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra
2020	J	`jnl`	Why distillation helps: a statistical perspective. CoRR Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar
2019	J	`jnl`	AdaCliP: Adaptive Clipping for Private SGD. CoRR Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2019	J	`jnl`	Are Transformers universal approximators of sequence-to-sequence functions? CoRR Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2019	A*	`conf`	Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces. NeurIPS Chuan Guo, Ali Mousavi, Xiang Wu, Daniel Niels Holtmann-Rice, Satyen Kale, Sashank J. Reddi, Sanjiv Kumar
2019	J	`jnl`	Efficient Inner Product Approximation in Hybrid Spaces. CoRR Xiang Wu, Ruiqi Guo, David Simcha, Dave Dopson, Sanjiv Kumar
2019	A*	`conf`	Escaping Saddle Points with Adaptive Gradient Methods. ICML Matthew Staib, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar, Suvrit Sra
2019	J	`jnl`	Escaping Saddle Points with Adaptive Gradient Methods. CoRR Matthew Staib, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar, Suvrit Sra
2019	A*	`conf`	Learning Adaptive Random Features. AAAI Yanjun Li, Kai Zhang, Jun Wang, Sanjiv Kumar
2019	A*	`conf`	Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling. ICML Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
2019	J	`jnl`	Learning to Learn by Zeroth-Order Oracle. CoRR Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh
2019	—	`conf`	Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks. ICLR (Poster) Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh
2019	J	`jnl`	Local Orthogonal Decomposition for Maximum Inner Product Search. CoRR Xiang Wu, Ruiqi Guo, Sanjiv Kumar, David Simcha
2019	J	`jnl`	Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise. CoRR Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
2019	J	`jnl`	New Loss Functions for Fast Maximum Inner Product Search. CoRR Ruiqi Guo, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar, Xiang Wu
2019	J	`jnl`	On the Convergence of Adam and Beyond. CoRR Sashank J. Reddi, Satyen Kale, Sanjiv Kumar
2019	J	`jnl`	Online Hierarchical Clustering Approximations. CoRR Aditya Krishna Menon, Anand Rajagopalan, Baris Sumengen, Gui Citovsky, Qin Cao, Sanjiv Kumar
2019	A	`conf`	Optimal Noise-Adding Mechanism in Additive Differential Privacy. AISTATS Quan Geng, Wei Ding, Ruiqi Guo, Sanjiv Kumar
2019	A*	`conf`	Sampled Softmax with Random Fourier Features. NeurIPS Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar
2019	J	`jnl`	Sampled Softmax with Random Fourier Features. CoRR Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar
2019	A	`conf`	Stochastic Negative Mining for Learning with Large Output Spaces. AISTATS Sashank J. Reddi, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Jiecao Chen, Sanjiv Kumar
2019	J	`jnl`	Why ADAM Beats SGD for Attention Models. CoRR Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra
2018	A*	`conf`	Adaptive Methods for Nonconvex Optimization. NeurIPS Manzil Zaheer, Sashank J. Reddi, Devendra Singh Sachan, Satyen Kale, Sanjiv Kumar
2018	J	`jnl`	Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks. CoRR Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh
2018	A*	`conf`	Loss Decomposition for Fast Learning in Large Output Spaces. ICML Ian En-Hsu Yen, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Sanjiv Kumar, Pradeep Ravikumar
2018	J	`jnl`	Nonlinear Online Learning with Adaptive Nyström Approximation. CoRR Si Si, Sanjiv Kumar, Yang Li
2018	—	`conf`	On the Convergence of Adam and Beyond. ICLR Sashank J. Reddi, Satyen Kale, Sanjiv Kumar
2018	J	`jnl`	Optimal Noise-Adding Mechanism in Additive Differential Privacy. CoRR Quan Geng, Wei Ding, Ruiqi Guo, Sanjiv Kumar
2018	J	`jnl`	Stochastic Negative Mining for Learning with Large Output Spaces. CoRR Sashank J. Reddi, Satyen Kale, Felix X. Yu, Daniel N. Holtmann-Rice, Jiecao Chen, Sanjiv Kumar
2018	J	`jnl`	The Sparse Recovery Autoencoder. CoRR Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
2018	J	`jnl`	Truncated Laplacian Mechanism for Approximate Differential Privacy. CoRR Quan Geng, Wei Ding, Ruiqi Guo, Sanjiv Kumar
2018	A*	`conf`	cpSGD: Communication-efficient and differentially-private distributed SGD. NeurIPS Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Brendan McMahan
2018	J	`jnl`	cpSGD: Communication-efficient and differentially-private distributed SGD. CoRR Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan
2017	A*	`conf`	Distributed Mean Estimation with Limited Communication. ICML Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan
2017	J	`jnl`	Efficient Natural Language Response Suggestion for Smart Reply. CoRR Matthew L. Henderson, Rami Al-Rfou, Brian Strope, Yun-Hsuan Sung, László Lukács, Ruiqi Guo, Sanjiv Kumar, Balint Miklos, Ray Kurzweil
2017	A	`conf`	Fast Classification with Binary Prototypes. AISTATS Kai Zhong, Ruiqi Guo, Sanjiv Kumar, Bowei Yan, David Simcha, Inderjit S. Dhillon
2017	A*	`conf`	Learning Spread-Out Local Feature Descriptors. ICCV Xu Zhang, Felix X. Yu, Sanjiv Kumar, Shih-Fu Chang
2017	J	`jnl`	Learning Spread-out Local Feature Descriptors. CoRR Xu Zhang, Felix X. Yu, Sanjiv Kumar, Shih-Fu Chang
2017	—	`conf`	Multiscale Quantization for Fast Similarity Search. NIPS Xiang Wu, Ruiqi Guo, Ananda Theertha Suresh, Sanjiv Kumar, Daniel N. Holtmann-Rice, David Simcha, Felix X. Yu
2017	J	`jnl`	Now Playing: Continuous low-power music recognition. CoRR Blaise Agüera y Arcas, Beat Gfeller, Ruiqi Guo, Kevin Kilgour, Sanjiv Kumar, James Lyon, Julian Odell, Marvin Ritter, Dominik Roblek, Matthew Sharifi, Mihajlo Velimirovic
2017	J	`jnl`	On Binary Embedding using Circulant Matrices. J. Mach. Learn. Res. Felix X. Yu, Aditya Bhaskara, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang
2017	A*	`conf`	Stochastic Generative Hashing. ICML Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song
2017	J	`jnl`	Stochastic Generative Hashing. CoRR Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song
2016	J	`jnl`	A Fast Approach to Solve Matrix Games with Payoffs of Trapezoidal Fuzzy Numbers. Asia Pac. J. Oper. Res. Sanjiv Kumar, Ritika Chopra, Ratnesh Rajan Saxena
2016	A*	`conf`	Binary embeddings with structured hashed projections. ICML Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun
2016	J	`jnl`	Distributed Mean Estimation with Limited Communication. CoRR Ananda Theertha Suresh, Felix X. Yu, H. Brendan McMahan, Sanjiv Kumar
2016	J	`jnl`	Learning to Hash for Indexing Big Data - A Survey. Proc. IEEE Jun Wang, Wei Liu, Sanjiv Kumar, Shih-Fu Chang
2016	—	`conf`	Orthogonal Random Features. NIPS Felix X. Yu, Ananda Theertha Suresh, Krzysztof Marcin Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar
2016	J	`jnl`	Orthogonal Random Features. CoRR Felix X. Yu, Ananda Theertha Suresh, Krzysztof Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar
2016	A	`conf`	Quantization based Fast Inner Product Search. AISTATS Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski, David Simcha
2016	J	`jnl`	Software-Defined Storage-Based Data Infrastructure Supportive of Hydroclimatology Simulation Containers: A Survey. Data Sci. Eng. Wonjun Lee, Sanjiv Kumar
2015	—	`conf`	A Survey of Modern Questions and Challenges in Feature Extraction. FE@NIPS Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
2015	A*	`conf`	An Exploration of Parameter Redundancy in Deep Networks with Circulant Projections. ICCV Yu Cheng, Felix X. Yu, Rogério Schmidt Feris, Sanjiv Kumar, Alok N. Choudhary, Shih-Fu Chang
2015	J	`jnl`	Binary embeddings with structured hashed projections. CoRR Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun
2015	J	`jnl`	Compact Nonlinear Maps and Circulant Extensions. CoRR Felix X. Yu, Sanjiv Kumar, Henry A. Rowley, Shih-Fu Chang
2015	Misc	`conf`	Exemplar-based large vocabulary speech recognition using k-nearest neighbors. ICASSP Yanbo Xu, Olivier Siohan, David Simcha, Sanjiv Kumar, Hank Liao
2015	—	`ch.`	Fast Binary Embedding for High-Dimensional Data. Multimedia Data Mining and Analytics Felix X. Yu, Yunchao Gong, Sanjiv Kumar
2015	J	`jnl`	Fast Neural Networks with Circulant Projections. CoRR Yu Cheng, Felix X. Yu, Rogério Schmidt Feris, Sanjiv Kumar, Alok N. Choudhary, Shih-Fu Chang
2015	J	`jnl`	Fast Online Clustering with Randomized Skeleton Sets. CoRR Krzysztof Choromanski, Sanjiv Kumar, Xiaofeng Liu
2015	A*	`conf`	Fast Orthogonal Projection Based on Kronecker Product. ICCV Xu Zhang, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar, Shengjin Wang, Shih-Fu Chang
2015	J	`jnl`	Learning to Hash for Indexing Big Data - A Survey. CoRR Jun Wang, Wei Liu, Sanjiv Kumar, Shih-Fu Chang
2015	J	`jnl`	On Binary Embedding using Circulant Matrices. CoRR Felix X. Yu, Aditya Bhaskara, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang
2015	J	`jnl`	Quantization based Fast Inner Product Search. CoRR Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski, David Simcha
2015	—	`conf`	Spherical Random Features for Polynomial Kernels. NIPS Jeffrey Pennington, Felix X. Yu, Sanjiv Kumar
2015	—	`conf`	Structured Transforms for Small-Footprint Deep Learning. NIPS Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar
2015	J	`jnl`	Structured Transforms for Small-Footprint Deep Learning. CoRR Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar
2014	A*	`conf`	Circulant Binary Embedding. ICML Felix X. Yu, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang
2014	J	`jnl`	Circulant Binary Embedding. CoRR Felix X. Yu, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang
2014	—	`conf`	Discrete Graph Hashing. NIPS Wei Liu, Cun Mu, Sanjiv Kumar, Shih-Fu Chang
2014	—	`ch.`	Discriminative Random Fields. Computer Vision, A Reference Guide Sanjiv Kumar
2014	J	`jnl`	On Learning with Label Proportions. CoRR Felix X. Yu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
2013	J	`jnl`	$\propto$SVM for learning with label proportions. CoRR Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
2013	J	`jnl`	Large-scale SVD and manifold learning. J. Mach. Learn. Res. Ameet Talwalkar, Sanjiv Kumar, Mehryar Mohri, Henry A. Rowley
2013	A*	`conf`	Learning Binary Codes for High-Dimensional Data Using Bilinear Projections. CVPR Yunchao Gong, Sanjiv Kumar, Henry A. Rowley, Svetlana Lazebnik
2013	—	`conf`	$\propto$SVM for Learning with Label Proportions. ICML (3) Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
2012	—	`conf`	Angular Quantization-based Binary Codes for Fast Similarity Search. NIPS Yunchao Gong, Sanjiv Kumar, Vishal Verma, Svetlana Lazebnik
2012	J	`jnl`	Compact Hyperplane Hashing with Bilinear Functions CoRR Wei Liu, Jun Wang, Yadong Mu, Sanjiv Kumar, Shih-Fu Chang
2012	A*	`conf`	Compact Hyperplane Hashing with Bilinear Functions. ICML Wei Liu, Jun Wang, Yadong Mu, Sanjiv Kumar, Shih-Fu Chang
2012	A*	`conf`	On the Difficulty of Nearest Neighbor Search. ICML Junfeng He, Sanjiv Kumar, Shih-Fu Chang
2012	J	`jnl`	Sampling Methods for the Nyström Method. J. Mach. Learn. Res. Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
2012	J	`jnl`	Semi-Supervised Hashing for Large-Scale Search. IEEE Trans. Pattern Anal. Mach. Intell. Jun Wang, Sanjiv Kumar, Shih-Fu Chang
2011	A*	`conf`	Hashing with Graphs. ICML Wei Liu, Jun Wang, Sanjiv Kumar, Shih-Fu Chang
2010	J	`jnl`	Baselines for Image Annotation. Int. J. Comput. Vis. Ameesh Makadia, Vladimir Pavlovic, Sanjiv Kumar
2010	—	`ch.`	Discriminative Graphical Models for Context-Based Classification. Computer Vision: Detection, Recognition and Reconstruction Sanjiv Kumar
2010	A*	`conf`	Sequential Projection Learning for Hashing with Compact Codes. ICML Jun Wang, Sanjiv Kumar, Shih-Fu Chang
2010	A*	`conf`	YouTubeCat: Learning to categorize wild web videos. CVPR Zheshen Wang, Ming Zhao, Yang Song, Sanjiv Kumar, Baoxin Li
2009	—	`conf`	Ensemble Nystrom Method. NIPS Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
2009	A*	`conf`	On sampling-based approximate spectral decomposition. ICML Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
2009	A	`conf`	Sampling Techniques for the Nystrom Method. AISTATS Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
2008	—	`conf`	A New Baseline for Image Annotation. ECCV (3) Ameesh Makadia, Vladimir Pavlovic, Sanjiv Kumar
2008	A*	`conf`	Face tracking and recognition with visual constraints in real-world videos. CVPR Minyoung Kim, Sanjiv Kumar, Vladimir Pavlovic, Henry A. Rowley
2008	A*	`conf`	Large-scale manifold learning. CVPR Ameet Talwalkar, Sanjiv Kumar, Henry A. Rowley
2007	A*	`conf`	Classification of Weakly-Labeled Data with Partial Equivalence Relations. ICCV Sanjiv Kumar, Henry A. Rowley
2006	J	`jnl`	Discriminative Random Fields. Int. J. Comput. Vis. Sanjiv Kumar, Martial Hebert
2005	A*	`conf`	A Hierarchical Field Framework for Unified Context-Based Classification. ICCV Sanjiv Kumar, Martial Hebert
2005	—	`conf`	Digital Tapestry. CVPR (1) Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov, Andrew Blake
2005	—	`conf`	Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study. EMMCVPR Sanjiv Kumar, Jonas August, Martial Hebert
2004	A	`conf`	Path planning with hallucinated worlds. IROS Bart C. Nabbe, Sanjiv Kumar, Martial Hebert
2003	J	`jnl`	An observation-constrained generative approach for probabilistic classification of image regions. Image Vis. Comput. Sanjiv Kumar, Alexander C. Loui, Martial Hebert
2003	—	`conf`	Discriminative Fields for Modeling Spatial Dependencies in Natural Images. NIPS Sanjiv Kumar, Martial Hebert
2003	A*	`conf`	Discriminative Random Fields: A Discriminative Framework for Contextual Interaction in Classification. ICCV Sanjiv Kumar, Martial Hebert
2003	—	`conf`	Man-Made Structure Detection in Natural Images using a Causal Multiscale Random Field. CVPR (1) Sanjiv Kumar, Martial Hebert
2000	J	`jnl`	A Fully Autonomous Microrobotic Endoscopy System. J. Intell. Robotic Syst. Vijayan K. Asari, Sanjiv Kumar, Irwan M. Kassim
2000	J	`jnl`	Design of a vision-guided microrobotic colonoscopy system. Adv. Robotics Sanjiv Kumar, Irwan M. Kassim, Vijayan K. Asari
1999	J	`jnl`	A New Approach for Nonlinear Distortion Correction in Endoscopic Images Based on Least Squares Estimation. IEEE Trans. Medical Imaging K. Vijayan Asari, Sanjiv Kumar, D. Radhakrishnan
1999	J	`jnl`	A pipelined architecture for image segmentation by adaptive progressive thresholding. Microprocess. Microsystems K. Vijayan Asari, Thambipillai Srikanthan, Sanjiv Kumar, D. Radhakrishnan