Aditya Krishna Menon

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 107

Top Venues

CoRR

ICLR

ICML

NeurIPS

University of California, San Diego, USA (PHD)

Education History

University of California, San Diego, USA

PHD

Publications

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)
Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar
Metric-aware LLM inference. 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)
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
Plugin estimators for selective classification with out-of-distribution detection. ICLR (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)
Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
The importance of feature preprocessing for differentially private linear optimization. ICLR (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)
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar
Learning to Reject Meets Long-tail Learning. ICLR (2024)
Vaishnavh Nagarajan, Aditya Krishna Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar
On student-teacher deviations in distillation: does it pay to disobey? NeurIPS (2023)
Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
The importance of feature preprocessing for differentially private linear optimization. CoRR (2023)
Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
When Does Confidence-Based Cascade Deferral Suffice? NeurIPS (2023)
Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
When Does Confidence-Based Cascade Deferral Suffice? CoRR (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)
Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon
Robust distillation for worst-class performance: on the interplay between teacher and student objectives. UAI (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)
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
Learning to reject meets OOD detection: Are all abstentions created equal? CoRR (2023)
Vaishnavh Nagarajan, Aditya Krishna Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar
On student-teacher deviations in distillation: does it pay to disobey? 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)
Arslan Chaudhry, Aditya Krishna Menon, Andreas Veit, Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar
When does mixup promote local linearity in learned representations? CoRR (2022)
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
Teacher's pet: understanding and mitigating biases in distillation. Trans. Mach. Learn. Res. 2022 (2022)
Marian-Andrei Rizoiu, Alexander Soen, Shidi Li, Pio Calderon, Leanne Dong, Aditya Krishna Menon, Lexing Xie
Interval-censored Hawkes processes. J. Mach. Learn. Res. 23 (2022)
Serena Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon
Robust Distillation for Worst-class Performance. 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)
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)
Harikrishna Narasimhan, Aditya Krishna Menon
Training Over-parameterized Models with Non-decomposable Objectives. NeurIPS (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)
Harikrishna Narasimhan, Aditya Krishna Menon
Training Over-parameterized Models with Non-decomposable Objectives. CoRR (2021)
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
Teacher's pet: understanding and mitigating biases in distillation. CoRR (2021)
Marian-Andrei Rizoiu, Alexander Soen, Shidi Li, Leanne Dong, Aditya Krishna Menon, Lexing Xie
Interval-censored Hawkes processes. CoRR (2021)
Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
Overparameterisation and worst-case generalisation: friend or foe? ICLR (2021)
Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, Evan Ettinger
Self-supervised Learning for Large-scale Item Recommendations. CIKM (2021)
Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou
Distilling Double Descent. CoRR (2021)
Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
Coping with Label Shift via Distributionally Robust Optimisation. ICLR (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)
Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Federated Learning with Only Positive Labels. ICML (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)
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
Does label smoothing mitigate label noise? CoRR (2020)
Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar
Why distillation helps: a statistical perspective. CoRR (2020)
Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi Kang, Evan Ettinger
Self-supervised Learning for Deep Models in Recommendations. CoRR (2020)
Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar
Semantic Label Smoothing for Sequence to Sequence Problems. EMNLP (1) (2020)
Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Robust Large-Margin Learning in Hyperbolic Space. CoRR (2020)
Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Robust large-margin learning in hyperbolic space. NeurIPS (2020)
Umanga Bista, Alexander Patrick Mathews, Aditya Krishna Menon, Lexing Xie
SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy. CoRR (2020)
Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar
Semantic Label Smoothing for Sequence to Sequence Problems. 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)
Richard Nock, Aditya Krishna Menon
Supervised learning: no loss no cry. ICML (2020)
Umanga Bista, Alexander Patrick Mathews, Aditya Krishna Menon, Lexing Xie
SupMMD: A Sentence Importance Model for Extractive Summarisation using Maximum Mean Discrepancy. EMNLP (Findings) (2020)
Richard Nock, Aditya Krishna Menon
Supervised Learning: No Loss No Cry. CoRR (2020)
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
Does label smoothing mitigate label noise? ICML (2020)
Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
Coping with Label Shift via Distributionally Robust Optimisation. CoRR (2020)
Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
Can gradient clipping mitigate label noise? ICLR (2020)
Robert C. Williamson, Aditya Krishna Menon
Fairness risk measures. CoRR (2019)
Alexandre Louis Lamy, Ziyuan Zhong, Aditya Krishna Menon, Nakul Verma
Noise-tolerant fair classification. CoRR (2019)
Umanga Bista, Alexander Patrick Mathews, Minjeong Shin, Aditya Krishna Menon, Lexing Xie
Comparative Document Summarisation via Classification. AAAI (2019)
Nan Lu, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data. ICLR (Poster) (2019)
Robert C. Williamson, Aditya Krishna Menon
Fairness risk measures. ICML (2019)
Takashi Ishida, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
Complementary-Label Learning for Arbitrary Losses and Models. ICML (2019)
Zac Cranko, Aditya Krishna Menon, Richard Nock, Cheng Soon Ong, Zhan Shi, Christian J. Walder
Monge blunts Bayes: Hardness Results for Adversarial Training. ICML (2019)
Dawei Chen, Cheng Soon Ong, Aditya Krishna Menon
Cold-start Playlist Recommendation with Multitask Learning. CoRR (2019)
Aditya Krishna Menon
The risk of trivial solutions in bipartite top ranking. Mach. Learn. 108 (4) (2019)
Aditya Krishna Menon, Anand Rajagopalan, Baris Sumengen, Gui Citovsky, Qin Cao, Sanjiv Kumar
Online Hierarchical Clustering Approximations. CoRR (2019)
Umanga Bista, Alexander Patrick Mathews, Minjeong Shin, Aditya Krishna Menon, Lexing Xie
Comparative Document Summarisation via Classification. CoRR (2018)
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
Anomaly Detection using One-Class Neural Networks. CoRR (2018)
Aditya Krishna Menon, Young Lee
Proper Loss Functions for Nonlinear Hawkes Processes. AAAI (2018)
Takashi Ishida, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
Complementary-Label Learning for Arbitrary Losses and Models. CoRR (2018)
Aditya Krishna Menon, Robert C. Williamson
The cost of fairness in binary classification. FAT (2018)
Dawei Chen, Cheng Soon Ong, Aditya Krishna Menon
Cold-start playlist recommendation with multitask learning. PeerJ Prepr. 6 (2018)
Aditya Krishna Menon, Brendan van Rooyen, Nagarajan Natarajan
Learning from binary labels with instance-dependent noise. Mach. Learn. 107 (8-10) (2018)
Nan Lu, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data. CoRR (2018)
Zac Cranko, Aditya Krishna Menon, Richard Nock, Cheng Soon Ong, Zhan Shi, Christian J. Walder
Monge beats Bayes: Hardness Results for Adversarial Training. CoRR (2018)
Richard Nock, Zac Cranko, Aditya Krishna Menon, Lizhen Qu, Robert C. Williamson
f-GANs in an Information Geometric Nutshell. NIPS (2017)
Dawei Chen, Dongwoo Kim, Lexing Xie, Minjeong Shin, Aditya Krishna Menon, Cheng Soon Ong, Iman Avazpour, John Grundy
PathRec: Visual Analysis of Travel Route Recommendations. RecSys (2017)
Aditya Krishna Menon, Dawei Chen, Lexing Xie, Cheng Soon Ong
Revisiting revisits in trajectory recommendation. CoRR (2017)
Aditya Krishna Menon, Robert C. Williamson
The cost of fairness in classification. CoRR (2017)
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
Robust, Deep and Inductive Anomaly Detection. ECML/PKDD (1) (2017)
Giorgio Patrini, Alessandro Rozza, Aditya Krishna Menon, Richard Nock, Lizhen Qu
Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach. CVPR (2017)
Aditya Krishna Menon, Young Lee
Predicting Short-Term Public Transport Demand via Inhomogeneous Poisson Processes. CIKM (2017)
Dawei Chen, Lexing Xie, Aditya Krishna Menon, Cheng Soon Ong
Structured Recommendation. CoRR (2017)
Richard Nock, Zac Cranko, Aditya Krishna Menon, Lizhen Qu, Robert C. Williamson
f-GANs in an Information Geometric Nutshell. CoRR (2017)
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
Robust, Deep and Inductive Anomaly Detection. CoRR (2017)
Dawei Chen, Dongwoo Kim, Lexing Xie, Minjeong Shin, Aditya Krishna Menon, Cheng Soon Ong, Iman Avazpour, John Grundy
PathRec: Visual Analysis of Travel Route Recommendations. CoRR (2017)
Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Lexing Xie, Darius Braziunas
Low-Rank Linear Cold-Start Recommendation from Social Data. AAAI (2017)
Aditya Krishna Menon, Dawei Chen, Lexing Xie, Cheng Soon Ong
Revisiting revisits in trajectory recommendation. CitRec@RecSys (2017)
Aditya Krishna Menon, Robert C. Williamson
Bipartite Ranking: a Risk-Theoretic Perspective. J. Mach. Learn. Res. 17 (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Aditya Krishna Menon