Ankit Singh Rawat

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 99

Top Venues

Publications

Nilesh Gupta, Devvrit, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon
Dual-Encoders for Extreme Multi-label Classification. ICLR (2024)
Muhammed Emrullah Ildiz, Yixiao Huang, Yingcong Li, Ankit Singh Rawat, Samet Oymak
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers. CoRR (2024)
Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal
DistillSpec: Improving Speculative Decoding via Knowledge Distillation. ICLR (2024)
Congchao Wang, Sean Augenstein, Keith Rush, Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Aditya Krishna Menon, Alec Go
Cascade-Aware Training of Language Models. CoRR (2024)
Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar
Faster Cascades via Speculative Decoding. CoRR (2024)
Yingcong Li, Yixiao Huang, Muhammed Emrullah Ildiz, Ankit Singh Rawat, Samet Oymak
Mechanics of Next Token Prediction with Self-Attention. CoRR (2024)
Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, Vaishnavh Nagarajan
Think before you speak: Training Language Models With Pause Tokens. ICLR (2024)
Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Language Model Cascades: Token-level uncertainty and beyond. CoRR (2024)
Yingcong Li, Yixiao Huang, Muhammed Emrullah Ildiz, Ankit Singh Rawat, Samet Oymak
Mechanics of Next Token Prediction with Self-Attention. AISTATS (2024)
Ziwei Ji, Himanshu Jain, Andreas Veit, Sashank J. Reddi, Sadeep Jayasumana, Ankit Singh Rawat, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar
Efficient Document Ranking with Learnable Late Interactions. CoRR (2024)
Yingcong Li, Ankit Singh Rawat, Samet Oymak
Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond. CoRR (2024)
Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Language Model Cascades: Token-Level Uncertainty And Beyond. ICLR (2024)
Michal Lukasik, Vaishnavh Nagarajan, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
What do larger image classifiers memorise? Trans. Mach. Learn. Res. 2024 (2024)
Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar
Large Language Models with Controllable Working Memory. ACL (Findings) (2023)
Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
When Does Confidence-Based Cascade Deferral Suffice? NeurIPS (2023)
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
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers. ICLR (2023)
Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
When Does Confidence-Based Cascade Deferral Suffice? CoRR (2023)
Samet Oymak, Ankit Singh Rawat, Mahdi Soltanolkotabi, Christos Thrampoulidis
On the Role of Attention in Prompt-tuning. ICML (2023)
Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal
DistillSpec: Improving Speculative Decoding via Knowledge Distillation. CoRR (2023)
Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, Vaishnavh Nagarajan
Think before you speak: Training Language Models With Pause Tokens. CoRR (2023)
Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar
EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval. CoRR (2023)
Hrayr Harutyunyan, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar
Supervision Complexity and its Role in Knowledge Distillation. CoRR (2023)
Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar
ResMem: Learn what you can and memorize the rest. CoRR (2023)
Michal Lukasik, Vaishnavh Nagarajan, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
What do larger image classifiers memorise? CoRR (2023)
Si Si, Felix X. Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar
Serving Graph Compression for Graph Neural Networks. ICLR (2023)
Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar
Teacher Guided Training: An Efficient Framework for Knowledge Transfer. ICLR (2023)
Soumya Basu, Ankit Singh Rawat, Manzil Zaheer
A Statistical Perspective on Retrieval-Based Models. ICML (2023)
Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar
ResMem: Learn what you can and memorize the rest. NeurIPS (2023)
Hrayr Harutyunyan, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar
Supervision Complexity and its Role in Knowledge Distillation. ICLR (2023)
Samet Oymak, Ankit Singh Rawat, Mahdi Soltanolkotabi, Christos Thrampoulidis
On the Role of Attention in Prompt-tuning. CoRR (2023)
Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
Post-hoc estimators for learning to defer to an expert. NeurIPS (2022)
Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
ELM: Embedding and Logit Margins for Long-Tail Learning. CoRR (2022)
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar
In defense of dual-encoders for neural ranking. ICML (2022)
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Kumar Avinava Dubey, Manzil Zaheer
A Fourier Approach to Mixture Learning. NeurIPS (2022)
Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar
Teacher Guided Training: An Efficient Framework for Knowledge Transfer. CoRR (2022)
Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix X. Chern, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar
Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers. CoRR (2022)
Soumya Basu, Ankit Singh Rawat, Manzil Zaheer
Generalization Properties of Retrieval-based Models. CoRR (2022)
Jianyu Wang, Hang Qi, Ankit Singh Rawat, Sashank J. Reddi, Sagar Waghmare, Felix X. Yu, Gauri Joshi
FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients. CoRR (2022)
Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar
Large Language Models with Controllable Working Memory. CoRR (2022)
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Avinava Dubey, Manzil Zaheer
A Fourier Approach to Mixture Learning. CoRR (2022)
Sashank J. Reddi, Rama Kumar Pasumarthi, Aditya Krishna Menon, Ankit Singh Rawat, Felix X. Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar
RankDistil: Knowledge Distillation for Ranking. AISTATS (2021)
Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Amr Ahmed, Sanjiv Kumar
When in Doubt, Summon the Titans: Efficient Inference with Large Models. CoRR (2021)
Saikiran Bulusu, Venkata Gandikota, Arya Mazumdar, Ankit Singh Rawat, Pramod K. Varshney
Byzantine Resilient Distributed Clustering with Redundant Data Assignment. ISIT (2021)
Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces. ICML (2021)
Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces. CoRR (2021)
Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
Overparameterisation and worst-case generalisation: friend or foe? ICLR (2021)
Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou
Distilling Double Descent. CoRR (2021)
Srinadh Bhojanapalli, Kimberly Wilber, Andreas Veit, Ankit Singh Rawat, Seungyeon Kim, Aditya Krishna Menon, Sanjiv Kumar
On the Reproducibility of Neural Network Predictions. CoRR (2021)
Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar
A statistical perspective on distillation. ICML (2021)
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
Long-tail learning via logit adjustment. ICLR (2021)
Chen Zhu, Ankit Singh Rawat, Manzil Zaheer, Srinadh Bhojanapalli, Daliang Li, Felix X. Yu, Sanjiv Kumar
Modifying Memories in Transformer Models. CoRR (2020)
Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Federated Learning with Only Positive Labels. ICML (2020)
Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
Low-Rank Bottleneck in Multi-head Attention Models. CoRR (2020)
Ankit Singh Rawat, Aditya Krishna Menon, Andreas Veit, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
Doubly-stochastic mining for heterogeneous retrieval. CoRR (2020)
Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar
Why distillation helps: a statistical perspective. CoRR (2020)
Venkata Gandikota, Arya Mazumdar, Ankit Singh Rawat
Reliable Distributed Clustering with Redundant Data Assignment. ISIT (2020)
Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan
Adversarial robustness via robust low rank representations. NeurIPS (2020)
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
Are Transformers universal approximators of sequence-to-sequence functions? ICLR (2020)
Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Robust Large-Margin Learning in Hyperbolic Space. CoRR (2020)
Venkata Gandikota, Arya Mazumdar, Ankit Singh Rawat
Reliable Distributed Clustering with Redundant Data Assignment. CoRR (2020)
Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
Low-Rank Bottleneck in Multi-head Attention Models. ICML (2020)
Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan
Adversarial robustness via robust low rank representations. CoRR (2020)
Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Robust large-margin learning in hyperbolic space. NeurIPS (2020)
Hardik B. Jain, Matthew Edwards, Ethan R. Elenberg, Ankit Singh Rawat, Sriram Vishwanath
Achieving Multi-port Memory Performance on Single-Port Memory with Coding Techniques. ICICT (2020)
Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
$O(n)$ Connections are Expressive Enough: Universal Approximability of Sparse Transformers. CoRR (2020)
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
Long-tail learning via logit adjustment. CoRR (2020)
Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Federated Learning with Only Positive Labels. CoRR (2020)
Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers. NeurIPS (2020)
Christos Thrampoulidis, Ankit Singh Rawat
The Generalized Lasso for Sub-Gaussian Measurements With Dithered Quantization. IEEE Trans. Inf. Theory 66 (4) (2020)
Hardik B. Jain, Matthew Edwards, Ethan R. Elenberg, Ankit Singh Rawat, Sriram Vishwanath
Achieving Multi-Port Memory Performance on Single-Port Memory with Coding Techniques. CoRR (2020)
Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
Can gradient clipping mitigate label noise? ICLR (2020)
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
Are Transformers universal approximators of sequence-to-sequence functions? CoRR (2019)
Raj Kumar Maity, Ankit Singh Rawat, Arya Mazumdar
Robust Gradient Descent via Moment Encoding and LDPC Codes. ISIT (2019)
Christos Thrampoulidis, Ankit Singh Rawat
Lifting high-dimensional non-linear models with Gaussian regressors. AISTATS (2019)
Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar
Sampled Softmax with Random Fourier Features. CoRR (2019)
Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar
Sampled Softmax with Random Fourier Features. NeurIPS (2019)
Arya Mazumdar, Ankit Singh Rawat
Learning and Recovery in the ReLU Model. Allerton (2019)
Ankit Singh Rawat, Onur Ozan Koyluoglu, Sriram Vishwanath
Centralized Repair of Multiple Node Failures With Applications to Communication Efficient Secret Sharing. IEEE Trans. Inf. Theory 64 (12) (2018)
Christos Thrampoulidis, Ankit Singh Rawat
The Generalized Lasso for Sub-gaussian Measurements with Dithered Quantization. CoRR (2018)
Ankit Singh Rawat, Itzhak Tamo, Venkatesan Guruswami, Klim Efremenko
MDS Code Constructions With Small Sub-Packetization and Near-Optimal Repair Bandwidth. IEEE Trans. Inf. Theory 64 (10) (2018)
Raj Kumar Maity, Ankit Singh Rawat, Arya Mazumdar
Robust Gradient Descent via Moment Encoding with LDPC Codes. CoRR (2018)
Arya Mazumdar, Ankit Singh Rawat
Representation Learning and Recovery in the ReLU Model. CoRR (2018)
Christos Thrampoulidis, Ankit Singh Rawat
The Generalized Lasso for Sub-gaussian Observations with Dithered Quantization. Allerton (2018)
Ankit Singh Rawat, Itzhak Tamo, Venkatesan Guruswami, Klim Efremenko
∊-MSR codes with small sub-packetization. ISIT (2017)
Arya Mazumdar, Ankit Singh Rawat
Associative Memory Using Dictionary Learning and Expander Decoding. AAAI (2017)
Ankit Singh Rawat, Itzhak Tamo, Venkatesan Guruswami, Klim Efremenko
MDS Code Constructions with Small Sub-packetization and Near-optimal Repair Bandwidth. CoRR (2017)
Venkatesan Guruswami, Ankit Singh Rawat
MDS Code Constructions with Small Sub-packetization and Near-optimal Repair Bandwidth. SODA (2017)
Islam Samy, Onur Ozan Koyluoglu, Ankit Singh Rawat
Efficient data access in hybrid cloud storage. Allerton (2017)
Ankit Singh Rawat
Secrecy capacity of minimum storage regenerating codes. ISIT (2017)
Ankit Singh Rawat, Dimitris S. Papailiopoulos, Alexandros G. Dimakis, Sriram Vishwanath
Locality and Availability in Distributed Storage. IEEE Trans. Inf. Theory 62 (8) (2016)
Ankit Singh Rawat, Onur Ozan Koyluoglu, Sriram Vishwanath
Progress on High-rate MSR Codes: Enabling Arbitrary Number of Helper Nodes. CoRR (2016)
Venkatesan Guruswami, Ankit Singh Rawat
New MDS codes with small sub-packetization and near-optimal repair bandwidth. CoRR (2016)
Ankit Singh Rawat, Onur Ozan Koyluoglu, Sriram Vishwanath
Centralized repair of multiple node failures. ISIT (2016)
Ankit Singh Rawat
A Note on Secure Minimum Storage Regenerating Codes. CoRR (2016)
Ankit Singh Rawat, Onur Ozan Koyluoglu, Sriram Vishwanath
Centralized Repair of Multiple Node Failures with Applications to Communication Efficient Secret Sharing. CoRR (2016)
Arya Mazumdar, Yury Polyanskiy, Ankit Singh Rawat, Hajir Roozbehani
Distance preserving maps and combinatorial joint source-channel coding for large alphabets. ISIT (2016)
Arya Mazumdar, Ankit Singh Rawat
Associative Memory using Dictionary Learning and Expander Decoding. CoRR (2016)
Ankit Singh Rawat, Zhao Song, Alexandros G. Dimakis, Anna Gál
Batch Codes Through Dense Graphs Without Short Cycles. IEEE Trans. Inf. Theory 62 (4) (2016)
Ankit Singh Rawat, Onur Ozan Koyluoglu, Sriram Vishwanath
Progress on high-rate MSR codes: Enabling arbitrary number of helper nodes. ITA (2016)
Arya Mazumdar, Ankit Singh Rawat
On adversarial joint source channel coding. ISIT (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ankit Singh Rawat