Aditya Krishna Menon

139 papers A* 43A 7Journal 73Unranked 15

Year	Rank	Type	Title / Venue / Authors
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	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`	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	J	`jnl`	Cascade-Aware Training of Language Models. CoRR Congchao Wang, Sean Augenstein, Keith Rush, Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Aditya Krishna Menon, Alec Go
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`	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`	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	A*	`conf`	Learning to Reject Meets Long-tail Learning. ICLR Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar
2024	J	`jnl`	Metric-aware LLM inference. CoRR Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, 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	—	`conf`	Regression Aware Inference with LLMs. EMNLP (Findings) Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar
2024	A*	`conf`	The importance of feature preprocessing for differentially private linear optimization. ICLR Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
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	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
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	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`	Learning to reject meets OOD detection: Are all abstentions created equal? CoRR Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
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	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`	Robust distillation for worst-class performance: on the interplay between teacher and student objectives. UAI Serena Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon
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	J	`jnl`	The importance of feature preprocessing for differentially private linear optimization. CoRR Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
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	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`	Interval-censored Hawkes processes. J. Mach. Learn. Res. Marian-Andrei Rizoiu, Alexander Soen, Shidi Li, Pio Calderon, Leanne Dong, Aditya Krishna Menon, Lexing Xie
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`	Robust Distillation for Worst-class Performance. CoRR Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon
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`	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	J	`jnl`	Distilling Double Descent. CoRR Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou
2021	J	`jnl`	Interval-censored Hawkes processes. CoRR Marian-Andrei Rizoiu, Alexander Soen, Shidi Li, Leanne Dong, Aditya Krishna Menon, Lexing Xie
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	A	`conf`	Self-supervised Learning for Large-scale Item Recommendations. CIKM 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
2021	J	`jnl`	Teacher's pet: understanding and mitigating biases in distillation. CoRR Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
2021	A*	`conf`	Training Over-parameterized Models with Non-decomposable Objectives. NeurIPS Harikrishna Narasimhan, Aditya Krishna Menon
2021	J	`jnl`	Training Over-parameterized Models with Non-decomposable Objectives. CoRR Harikrishna Narasimhan, Aditya Krishna Menon
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	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	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	J	`jnl`	Long-tail learning via logit adjustment. CoRR Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, 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	J	`jnl`	Self-supervised Learning for Deep Models in Recommendations. CoRR Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi Kang, Evan Ettinger
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	—	`conf`	SupMMD: A Sentence Importance Model for Extractive Summarisation using Maximum Mean Discrepancy. EMNLP (Findings) Umanga Bista, Alexander Patrick Mathews, Aditya Krishna Menon, Lexing Xie
2020	J	`jnl`	SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy. CoRR Umanga Bista, Alexander Patrick Mathews, Aditya Krishna Menon, Lexing Xie
2020	J	`jnl`	Supervised Learning: No Loss No Cry. CoRR Richard Nock, Aditya Krishna Menon
2020	A*	`conf`	Supervised learning: no loss no cry. ICML Richard Nock, Aditya Krishna Menon
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`	Cold-start Playlist Recommendation with Multitask Learning. CoRR Dawei Chen, Cheng Soon Ong, Aditya Krishna Menon
2019	A*	`conf`	Comparative Document Summarisation via Classification. AAAI Umanga Bista, Alexander Patrick Mathews, Minjeong Shin, Aditya Krishna Menon, Lexing Xie
2019	A*	`conf`	Complementary-Label Learning for Arbitrary Losses and Models. ICML Takashi Ishida, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
2019	A*	`conf`	Fairness risk measures. ICML Robert C. Williamson, Aditya Krishna Menon
2019	J	`jnl`	Fairness risk measures. CoRR Robert C. Williamson, Aditya Krishna Menon
2019	A*	`conf`	Monge blunts Bayes: Hardness Results for Adversarial Training. ICML Zac Cranko, Aditya Krishna Menon, Richard Nock, Cheng Soon Ong, Zhan Shi, Christian J. Walder
2019	J	`jnl`	Noise-tolerant fair classification. CoRR Alexandre Louis Lamy, Ziyuan Zhong, Aditya Krishna Menon, Nakul Verma
2019	—	`conf`	On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data. ICLR (Poster) Nan Lu, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
2019	J	`jnl`	Online Hierarchical Clustering Approximations. CoRR Aditya Krishna Menon, Anand Rajagopalan, Baris Sumengen, Gui Citovsky, Qin Cao, Sanjiv Kumar
2019	J	`jnl`	The risk of trivial solutions in bipartite top ranking. Mach. Learn. Aditya Krishna Menon
2018	J	`jnl`	Anomaly Detection using One-Class Neural Networks. CoRR Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
2018	J	`jnl`	Cold-start playlist recommendation with multitask learning. PeerJ Prepr. Dawei Chen, Cheng Soon Ong, Aditya Krishna Menon
2018	J	`jnl`	Comparative Document Summarisation via Classification. CoRR Umanga Bista, Alexander Patrick Mathews, Minjeong Shin, Aditya Krishna Menon, Lexing Xie
2018	J	`jnl`	Complementary-Label Learning for Arbitrary Losses and Models. CoRR Takashi Ishida, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
2018	J	`jnl`	Learning from binary labels with instance-dependent noise. Mach. Learn. Aditya Krishna Menon, Brendan van Rooyen, Nagarajan Natarajan
2018	J	`jnl`	Monge beats Bayes: Hardness Results for Adversarial Training. CoRR Zac Cranko, Aditya Krishna Menon, Richard Nock, Cheng Soon Ong, Zhan Shi, Christian J. Walder
2018	J	`jnl`	On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data. CoRR Nan Lu, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
2018	A*	`conf`	Proper Loss Functions for Nonlinear Hawkes Processes. AAAI Aditya Krishna Menon, Young Lee
2018	—	`conf`	The cost of fairness in binary classification. FAT Aditya Krishna Menon, Robert C. Williamson
2017	A*	`conf`	Low-Rank Linear Cold-Start Recommendation from Social Data. AAAI Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Lexing Xie, Darius Braziunas
2017	A*	`conf`	Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach. CVPR Giorgio Patrini, Alessandro Rozza, Aditya Krishna Menon, Richard Nock, Lizhen Qu
2017	A	`conf`	PathRec: Visual Analysis of Travel Route Recommendations. RecSys Dawei Chen, Dongwoo Kim, Lexing Xie, Minjeong Shin, Aditya Krishna Menon, Cheng Soon Ong, Iman Avazpour, John Grundy
2017	J	`jnl`	PathRec: Visual Analysis of Travel Route Recommendations. CoRR Dawei Chen, Dongwoo Kim, Lexing Xie, Minjeong Shin, Aditya Krishna Menon, Cheng Soon Ong, Iman Avazpour, John Grundy
2017	A	`conf`	Predicting Short-Term Public Transport Demand via Inhomogeneous Poisson Processes. CIKM Aditya Krishna Menon, Young Lee
2017	—	`conf`	Revisiting revisits in trajectory recommendation. CitRec@RecSys Aditya Krishna Menon, Dawei Chen, Lexing Xie, Cheng Soon Ong
2017	J	`jnl`	Revisiting revisits in trajectory recommendation. CoRR Aditya Krishna Menon, Dawei Chen, Lexing Xie, Cheng Soon Ong
2017	—	`conf`	Robust, Deep and Inductive Anomaly Detection. ECML/PKDD (1) Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
2017	J	`jnl`	Robust, Deep and Inductive Anomaly Detection. CoRR Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
2017	J	`jnl`	Structured Recommendation. CoRR Dawei Chen, Lexing Xie, Aditya Krishna Menon, Cheng Soon Ong
2017	J	`jnl`	The cost of fairness in classification. CoRR Aditya Krishna Menon, Robert C. Williamson
2017	—	`conf`	f-GANs in an Information Geometric Nutshell. NIPS Richard Nock, Zac Cranko, Aditya Krishna Menon, Lizhen Qu, Robert C. Williamson
2017	J	`jnl`	f-GANs in an Information Geometric Nutshell. CoRR Richard Nock, Zac Cranko, Aditya Krishna Menon, Lizhen Qu, Robert C. Williamson
2016	—	`conf`	A scaled Bregman theorem with applications. NIPS Richard Nock, Aditya Krishna Menon, Cheng Soon Ong
2016	J	`jnl`	A scaled Bregman theorem with applications. CoRR Richard Nock, Aditya Krishna Menon, Cheng Soon Ong
2016	J	`jnl`	Bipartite Ranking: a Risk-Theoretic Perspective. J. Mach. Learn. Res. Aditya Krishna Menon, Robert C. Williamson
2016	J	`jnl`	Learning from Binary Labels with Instance-Dependent Corruption. CoRR Aditya Krishna Menon, Brendan van Rooyen, Nagarajan Natarajan
2016	A*	`conf`	Linking losses for density ratio and class-probability estimation. ICML Aditya Krishna Menon, Cheng Soon Ong
2016	J	`jnl`	Making Neural Networks Robust to Label Noise: a Loss Correction Approach. CoRR Giorgio Patrini, Alessandro Rozza, Aditya Krishna Menon, Richard Nock, Lizhen Qu
2016	A*	`conf`	On the Effectiveness of Linear Models for One-Class Collaborative Filtering. AAAI Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Darius Braziunas
2016	A*	`conf`	Practical Linear Models for Large-Scale One-Class Collaborative Filtering. IJCAI Suvash Sedhain, Hung Bui, Jaya Kawale, Nikos Vlassis, Branislav Kveton, Aditya Krishna Menon, Trung Bui, Scott Sanner
2015	J	`jnl`	An Average Classification Algorithm. CoRR Brendan van Rooyen, Aditya Krishna Menon
2015	—	`conf`	AutoRec: Autoencoders Meet Collaborative Filtering. WWW (Companion Volume) Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Lexing Xie
2015	A	`conf`	Cross-Modal Retrieval: A Pairwise Classification Approach. SDM Aditya Krishna Menon, Didi Surian, Sanjay Chawla
2015	A*	`conf`	Learning from Corrupted Binary Labels via Class-Probability Estimation. ICML Aditya Krishna Menon, Brendan van Rooyen, Cheng Soon Ong, Bob Williamson
2015	—	`conf`	Learning with Symmetric Label Noise: The Importance of Being Unhinged. NIPS Brendan van Rooyen, Aditya Krishna Menon, Robert C. Williamson
2015	J	`jnl`	Learning with Symmetric Label Noise: The Importance of Being Unhinged. CoRR Brendan van Rooyen, Aditya Krishna Menon, Robert C. Williamson
2014	A*	`conf`	Bayes-Optimal Scorers for Bipartite Ranking. COLT Aditya Krishna Menon, Robert C. Williamson
2014	J	`jnl`	Detecting inappropriate access to electronic health records using collaborative filtering. Mach. Learn. Aditya Krishna Menon, Xiaoqian Jiang, Jihoon Kim, Jaideep Vaidya, Lucila Ohno-Machado
2013	—	`conf`	A Machine Learning Framework for Programming by Example. ICML (1) Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani, Butler W. Lampson, Adam Kalai
2013	A*	`conf`	A colorful approach to text processing by example. UIST Kuat Yessenov, Shubham Tulsiani, Aditya Krishna Menon, Robert C. Miller, Sumit Gulwani, Butler W. Lampson, Adam Kalai
2013	J	`jnl`	Beam search algorithms for multilabel learning. Mach. Learn. Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan
2013	—	`—`	Latent feature models for dyadic prediction /. Aditya Krishna Menon
2013	—	`conf`	On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance. ICML (3) Aditya Krishna Menon, Harikrishna Narasimhan, Shivani Agarwal, Sanjay Chawla
2012	—	`conf`	Learning and Inference in Probabilistic Classifier Chains with Beam Search. ECML/PKDD (1) Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan
2012	J	`jnl`	Predicting accurate probabilities with a ranking loss CoRR Aditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, Lucila Ohno-Machado
2012	A*	`conf`	Predicting accurate probabilities with a ranking loss. ICML Aditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, Lucila Ohno-Machado
2012	J	`jnl`	Textual Features for Programming by Example CoRR Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani, Butler W. Lampson, Adam Tauman Kalai
2011	J	`jnl`	Fast Algorithms for Approximating the Singular Value Decomposition. ACM Trans. Knowl. Discov. Data Aditya Krishna Menon, Charles Elkan
2011	—	`conf`	Link Prediction via Matrix Factorization. ECML/PKDD (2) Aditya Krishna Menon, Charles Elkan
2011	A*	`conf`	Response prediction using collaborative filtering with hierarchies and side-information. KDD Aditya Krishna Menon, Krishna Prasad Chitrapura, Sachin Garg, Deepak Agarwal, Nagaraj Kota
2010	A*	`conf`	A Log-Linear Model with Latent Features for Dyadic Prediction. ICDM Aditya Krishna Menon, Charles Elkan
2010	J	`jnl`	Dyadic Prediction Using a Latent Feature Log-Linear Model CoRR Aditya Krishna Menon, Charles Elkan
2010	J	`jnl`	Predicting labels for dyadic data. Data Min. Knowl. Discov. Aditya Krishna Menon, Charles Elkan
2007	A	`conf`	An incremental data-stream sketch using sparse random projections. SDM Aditya Krishna Menon, Gia Vinh Anh Pham, Sanjay Chawla, Anastasios Viglas