Sanjiv Kumar
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
89
Venues
12
Active years
2003–2025
Best venue rank
A*
Where they publish
Papers
89 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Better autoregressive regression with LLMs via regression-aware fine-tuning. | Michal Lukasik, Zhao Meng, Harikrishna Narasimhan, Yin-Wen Chang, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar |
| 2025 | ICLR | Faster Cascades via Speculative Decoding. | Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar |
| 2025 | ICLR | Efficient stagewise pretraining via progressive subnetworks. | Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar |
| 2025 | ICLR | Reasoning with Latent Thoughts: On the Power of Looped Transformers. | Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, Sanjiv Kumar, Sashank J. Reddi |
| 2025 | ICLR | LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. | Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar |
| 2025 | ICML | Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation. | Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, MohammadHossein Bateni, Sanjiv Kumar |
| 2025 | ICML | LAuReL: Learned Augmented Residual Layer. | Gaurav Menghani, Ravi Kumar, Sanjiv Kumar |
| 2025 | ICML | Structured Preconditioners in Adaptive Optimization: A Unified Analysis. | Shuo Xie, Tianhao Wang, Sashank J. Reddi, Sanjiv Kumar, Zhiyuan Li |
| 2024 | CVPR | MarkovGen: Structured Prediction for Efficient Text-to-Image Generation. | Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar |
| 2024 | CVPR | Rethinking FID: Towards a Better Evaluation Metric for Image Generation. | Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar |
| 2024 | EMNLP | Regression Aware Inference with LLMs. | Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar |
| 2024 | ICLR | On Bias-Variance Alignment in Deep Models. | Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar |
| 2024 | ICLR | Think before you speak: Training Language Models With Pause Tokens. | Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, Vaishnavh Nagarajan |
| 2024 | ICLR | Language Model Cascades: Token-Level Uncertainty And Beyond. | Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar |
| 2024 | ICLR | Functional Interpolation for Relative Positions improves Long Context Transformers. | Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontan, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli |
| 2024 | ICLR | Learning to Reject Meets Long-tail Learning. | Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar |
| 2024 | ICLR | Plugin estimators for selective classification with out-of-distribution detection. | Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar |
| 2024 | ICLR | Two-stage LLM Fine-tuning with Less Specialization and More Generalization. | Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar |
| 2024 | ICLR | DistillSpec: Improving Speculative Decoding via Knowledge Distillation. | Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-Franois Kagy, Rishabh Agarwal |
| 2024 | ICML | Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning? | Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar |
| 2024 | ICML | USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval. | Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar |
| 2024 | ICML | Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines. | Yuchen Li, Alexandre Kirchmeyer, Aashay Mehta, Yilong Qin, Boris Dadachev, Kishore Papineni, Sanjiv Kumar, Andrej Risteski |
| 2024 | ICML | Tandem Transformers for Inference Efficient LLMs. | Aishwarya P. S., Pranav Ajit Nair, Yashas Samaga, Toby Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli |
| 2023 | ACL | Large Language Models with Controllable Working Memory. | Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar |
| 2023 | ICLR | Leveraging Importance Weights in Subset Selection. | Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang |
| 2023 | ICLR | Supervision Complexity and its Role in Knowledge Distillation. | Hrayr Harutyunyan, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar |
| 2023 | ICLR | The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers. | 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 | ICLR | Serving Graph Compression for Graph Neural Networks. | Si Si, Felix X. Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar |
| 2023 | ICLR | Automating Nearest Neighbor Search Configuration with Constrained Optimization. | Philip Sun, Ruiqi Guo, Sanjiv Kumar |
| 2023 | ICLR | Teacher Guided Training: An Efficient Framework for Knowledge Transfer. | Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar |
| 2023 | ICML | Efficient Training of Language Models using Few-Shot Learning. | Sashank J. Reddi, Sobhan Miryoosefi, Stefani Karp, Shankar Krishnan, Satyen Kale, Seungyeon Kim, Sanjiv Kumar |
| 2023 | ICMLA | A Framework for Developing the Next Generation Interactive Soil Moisture Forecasting System Using the Long-Short Term Memory Model. | Guna Shekar M., Wonjun Lee, Sanjiv Kumar, Yanan Duan, Imtiaz Rangwala |
| 2022 | ICML | Robust Training of Neural Networks Using Scale Invariant Architectures. | Zhiyuan Li, Srinadh Bhojanapalli, Manzil Zaheer, Sashank J. Reddi, Sanjiv Kumar |
| 2022 | ICML | In defense of dual-encoders for neural ranking. | Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar |
| 2021 | AISTATS | RankDistil: Knowledge Distillation for Ranking. | Sashank J. Reddi, Rama Kumar Pasumarthi, Aditya Krishna Menon, Ankit Singh Rawat, Felix X. Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar |
| 2021 | ICLR | Evaluations and Methods for Explanation through Robustness Analysis. | Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Kumar Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh |
| 2021 | ICLR | Long-tail learning via logit adjustment. | Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar |
| 2021 | ICLR | Overparameterisation and worst-case generalisation: friend or foe? | Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar |
| 2021 | ICLR | Adaptive Federated Optimization. | Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konecn, Sanjiv Kumar, Hugh Brendan McMahan |
| 2021 | ICLR | Coping with Label Shift via Distributionally Robust Optimisation. | Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra |
| 2021 | ICML | A statistical perspective on distillation. | Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar |
| 2021 | ICML | Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces. | Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar |
| 2020 | AISTATS | Tight Analysis of Privacy and Utility Tradeoff in Approximate Differential Privacy. | Quan Geng, Wei Ding, Ruiqi Guo, Sanjiv Kumar |
| 2020 | CVPR | How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework. | Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh |
| 2020 | EMNLP | Semantic Label Smoothing for Sequence to Sequence Problems. | Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar |
| 2020 | ICLR | Pre-training Tasks for Embedding-based Large-scale Retrieval. | Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar |
| 2020 | ICLR | Can gradient clipping mitigate label noise? | Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar |
| 2020 | ICLR | Learning to Learn by Zeroth-Order Oracle. | Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh |
| 2020 | ICLR | Large Batch Optimization for Deep Learning: Training BERT in 76 minutes. | Yang You, Jing Li, Sashank J. Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, Cho-Jui Hsieh |
| 2020 | ICLR | Are Transformers universal approximators of sequence-to-sequence functions? | Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar |
| 2020 | ICML | Low-Rank Bottleneck in Multi-head Attention Models. | Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar |
| 2020 | ICML | Accelerating Large-Scale Inference with Anisotropic Vector Quantization. | Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar |
| 2020 | ICML | Does label smoothing mitigate label noise? | Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar |
| 2020 | ICML | Federated Learning with Only Positive Labels. | Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar |
| 2019 | AAAI | Learning Adaptive Random Features. | Yanjun Li, Kai Zhang, Jun Wang, Sanjiv Kumar |
| 2019 | AISTATS | Optimal Noise-Adding Mechanism in Additive Differential Privacy. | Quan Geng, Wei Ding, Ruiqi Guo, Sanjiv Kumar |
| 2019 | AISTATS | Stochastic Negative Mining for Learning with Large Output Spaces. | Sashank J. Reddi, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Jiecao Chen, Sanjiv Kumar |
| 2019 | ICLR | Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks. | Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh |
| 2019 | ICML | Escaping Saddle Points with Adaptive Gradient Methods. | Matthew Staib, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar, Suvrit Sra |
| 2019 | ICML | Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling. | Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar |
| 2018 | ICLR | On the Convergence of Adam and Beyond. | Sashank J. Reddi, Satyen Kale, Sanjiv Kumar |
| 2018 | ICML | Loss Decomposition for Fast Learning in Large Output Spaces. | Ian En-Hsu Yen, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Sanjiv Kumar, Pradeep Ravikumar |
| 2017 | AISTATS | Fast Classification with Binary Prototypes. | Kai Zhong, Ruiqi Guo, Sanjiv Kumar, Bowei Yan, David Simcha, Inderjit S. Dhillon |
| 2017 | ICCV | Learning Spread-Out Local Feature Descriptors. | Xu Zhang, Felix X. Yu, Sanjiv Kumar, Shih-Fu Chang |
| 2017 | ICML | Stochastic Generative Hashing. | Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song |
| 2017 | ICML | Distributed Mean Estimation with Limited Communication. | Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan |
| 2016 | AISTATS | Quantization based Fast Inner Product Search. | Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski, David Simcha |
| 2016 | ICML | Binary embeddings with structured hashed projections. | Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun |
| 2015 | ICASSP | Exemplar-based large vocabulary speech recognition using k-nearest neighbors. | Yanbo Xu, Olivier Siohan, David Simcha, Sanjiv Kumar, Hank Liao |
| 2015 | ICCV | An Exploration of Parameter Redundancy in Deep Networks with Circulant Projections. | Yu Cheng, Felix X. Yu, Rogrio Schmidt Feris, Sanjiv Kumar, Alok N. Choudhary, Shih-Fu Chang |
| 2015 | ICCV | Fast Orthogonal Projection Based on Kronecker Product. | Xu Zhang, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar, Shengjin Wang, Shih-Fu Chang |
| 2014 | ICML | Circulant Binary Embedding. | Felix X. Yu, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang |
| 2013 | CVPR | Learning Binary Codes for High-Dimensional Data Using Bilinear Projections. | Yunchao Gong, Sanjiv Kumar, Henry A. Rowley, Svetlana Lazebnik |
| 2013 | ICML | \(\propto\)SVM for Learning with Label Proportions. | Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang |
| 2012 | ICML | On the Difficulty of Nearest Neighbor Search. | Junfeng He, Sanjiv Kumar, Shih-Fu Chang |
| 2012 | ICML | Compact Hyperplane Hashing with Bilinear Functions. | Wei Liu, Jun Wang, Yadong Mu, Sanjiv Kumar, Shih-Fu Chang |
| 2011 | ICML | Hashing with Graphs. | Wei Liu, Jun Wang, Sanjiv Kumar, Shih-Fu Chang |
| 2010 | CVPR | YouTubeCat: Learning to categorize wild web videos. | Zheshen Wang, Ming Zhao, Yang Song, Sanjiv Kumar, Baoxin Li |
| 2010 | ICML | Sequential Projection Learning for Hashing with Compact Codes. | Jun Wang, Sanjiv Kumar, Shih-Fu Chang |
| 2009 | ICML | On sampling-based approximate spectral decomposition. | Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar |
| 2008 | CVPR | Face tracking and recognition with visual constraints in real-world videos. | Minyoung Kim, Sanjiv Kumar, Vladimir Pavlovic, Henry A. Rowley |
| 2008 | CVPR | Large-scale manifold learning. | Ameet Talwalkar, Sanjiv Kumar, Henry A. Rowley |
| 2008 | ECCV | A New Baseline for Image Annotation. | Ameesh Makadia, Vladimir Pavlovic, Sanjiv Kumar |
| 2007 | ICCV | Classification of Weakly-Labeled Data with Partial Equivalence Relations. | Sanjiv Kumar, Henry A. Rowley |
| 2005 | CVPR | Digital Tapestry. | Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov, Andrew Blake |
| 2005 | ICCV | A Hierarchical Field Framework for Unified Context-Based Classification. | Sanjiv Kumar, Martial Hebert |
| 2004 | IROS | Path planning with hallucinated worlds. | Bart C. Nabbe, Sanjiv Kumar, Martial Hebert |
| 2003 | CVPR | Man-Made Structure Detection in Natural Images using a Causal Multiscale Random Field. | Sanjiv Kumar, Martial Hebert |
| 2003 | ICCV | Discriminative Random Fields: A Discriminative Framework for Contextual Interaction in Classification. | Sanjiv Kumar, Martial Hebert |