A. Menon

发表

Multilabel reductions: what is my loss optimising?

Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar, 2019, NeurIPS.

Doubly-stochastic mining for heterogeneous retrieval pdf

Sanjiv Kumar, Ankit Singh Rawat, Sashank J. Reddi, 2020, ArXiv.

Fairness risk measures

R. C. Williamson, A. Menon, 2019, ICML.

Why distillation helps: a statistical perspective pdf

Ankit Singh Rawat, Sashank J. Reddi, Aditya Krishna Menon, 2020, ArXiv.

Robust Large-Margin Learning in Hyperbolic Space pdf

Sanjiv Kumar, Ankit Singh Rawat, Manzil Zaheer, 2020, NeurIPS.

Can gradient clipping mitigate label noise?

Ankit Singh Rawat, Sashank J. Reddi, Aditya Krishna Menon, 2020, ICLR.

Link Prediction via Matrix Factorization

Charles Elkan, Aditya Krishna Menon, C. Elkan, 2011, ECML/PKDD.

Learning with Symmetric Label Noise: The Importance of Being Unhinged

Aditya Krishna Menon, Robert C. Williamson, Brendan van Rooyen, 2015, NIPS.

Learning from Corrupted Binary Labels via Class-Probability Estimation

Cheng Soon Ong, Aditya Krishna Menon, Brendan van Rooyen, 2015, ICML.

Noise-tolerant fair classification

Aditya Krishna Menon, Nakul Verma, Ziyuan Zhong, 2019, NeurIPS.

Dyadic Prediction Using a Latent Feature Log-Linear Model pdf

Charles Elkan, Aditya Krishna Menon, C. Elkan, 2010, ArXiv.

Faster Johnson-Lindenstrauss style reductions

A. Menon, 2007 .

AN INVESTIGATION OF POSITIONING ACCURACY TRANSMITTED BY 1 CONNECTED HEAVY VEHICLES USING DSRC 2 3 4

A. Menon, Yuming Ou, P. Tyler, 2016 .

ELM: Embedding and Logit Margins for Long-Tail Learning

Wittawat Jitkrittum, A. Menon, A. Rawat, 2022, ArXiv.

Long-tail learning via logit adjustment pdf

Ankit Singh Rawat, Aditya Krishna Menon, Andreas Veit, 2020, ICLR.

An Approach to Sparse, Fine-Grained OD Estimation

Aditya Krishna Menon, Chen Cai, Fang Chen, 2015 .

A statistical perspective on distillation

Ankit Singh Rawat, Sashank J. Reddi, Aditya Krishna Menon, 2021, ICML.

Cold-start playlist recommendation with multitask learning

Cheng Soon Ong, Dawei Chen, Aditya Krishna Menon, 2018 .

In defense of dual-encoders for neural ranking

Sashank J. Reddi, A. Menon, A. Rawat, 2022, ICML.

Interval-censored Hawkes processes

A. Menon, Lexing Xie, Marian-Andrei Rizoiu, 2021, J. Mach. Learn. Res..

Bayes-Optimal Scorers for Bipartite Ranking

Aditya Krishna Menon, Robert C. Williamson, R. C. Williamson, 2014, COLT.

EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval

R. Fergus, M. Zaheer, Wittawat Jitkrittum, 2023, ArXiv.

Disentangling Labeling and Sampling Bias for Learning in Large-output Spaces

Sashank J. Reddi, Felix X. Yu, Wittawat Jitkrittum, 2021 .

Learning from binary labels with instance-dependent noise

Nagarajan Natarajan, Aditya Krishna Menon, Brendan van Rooyen, 2018, Machine Learning.

On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance

Sanjay Chawla, Harikrishna Narasimhan, Shivani Agarwal, 2013, ICML.

Long-tail learning via logit adjustment pdf

Ankit Singh Rawat, Aditya Krishna Menon, Andreas Veit, 2020, ICLR.

Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach

Richard Nock, Alessandro Rozza, Lizhen Qu, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

AutoRec: Autoencoders Meet Collaborative Filtering

Scott Sanner, Lexing Xie, Aditya Krishna Menon, 2015, WWW.

On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data pdf

Gang Niu, Masashi Sugiyama, Aditya Krishna Menon, 2018, ICLR.

Bipartite Ranking: a Risk-Theoretic Perspective

Aditya Krishna Menon, Robert C. Williamson, R. C. Williamson, 2016, J. Mach. Learn. Res..

RankDistil: Knowledge Distillation for Ranking

Ankit Singh Rawat, Sashank J. Reddi, Aditya Krishna Menon, 2021, AISTATS.

A loss framework for calibrated anomaly detection

Aditya Krishna Menon, Robert C. Williamson, R. C. Williamson, 2018, NeurIPS.

Self-supervised Learning for Large-scale Item Recommendations

Jieqi Kang, Ting Chen, Ed H. Chi, 2020, CIKM.

Fine-grained OD estimation with automated zoning and sparsity regularisation

Weihong Wang, Tao Wen, Aditya Krishna Menon, 2015 .

Training Over-parameterized Models with Non-decomposable Objectives pdf

Harikrishna Narasimhan, Aditya Krishna Menon, A. Menon, 2021, NeurIPS.

f-GANs in an Information Geometric Nutshell

Richard Nock, Lizhen Qu, Aditya Krishna Menon, 2017, NIPS.

Linking losses for density ratio and class-probability estimation

Cheng Soon Ong, Aditya Krishna Menon, A. Menon, 2016, ICML.

Teacher's pet: understanding and mitigating biases in distillation pdf

Aditya Krishna Menon, Michal Lukasik, Srinadh Bhojanapalli, 2021, Trans. Mach. Learn. Res..

Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces

Ankit Singh Rawat, Sashank J. Reddi, Wittawat Jitkrittum, 2021, ICML.

Anomaly Detection using One-Class Neural Networks pdf

Sanjay Chawla, Aditya Krishna Menon, Raghavendra Chalapathy, 2018, ArXiv.

Robust Distillation for Worst-class Performance

A. Menon, Sara Hooker, Serena Wang, 2022, ArXiv.

Large-Scale Support Vector Machines: Algorithms and Theory

Aditya Krishna Menon, A. Menon, 2009 .

Coping with Label Shift via Distributionally Robust Optimisation pdf

Suvrit Sra, Andreas Veit, Jingzhao Zhang, 2020, ICLR.

Proper Loss Functions for Nonlinear Hawkes Processes

Young Lee, Aditya Krishna Menon, A. Menon, 2018, AAAI.

Predicting Short-Term Public Transport Demand via Inhomogeneous Poisson Processes

Aditya Krishna Menon, Young Lee, A. Menon, 2017, CIKM.

The cost of fairness in binary classification

Aditya Krishna Menon, Robert C. Williamson, R. C. Williamson, 2018, FAT.

Federated Learning with Only Positive Labels

Sanjiv Kumar, Ankit Singh Rawat, Aditya Krishna Menon, 2020, ICML.

Overparameterisation and worst-case generalisation: friend or foe?

Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, 2021, ICLR.

Predicting accurate probabilities with a ranking loss

Xiaoqian Jiang, Lucila Ohno-Machado, Charles Elkan, 2012, ICML.

Does label smoothing mitigate label noise?

Aditya Krishna Menon, Michal Lukasik, Srinadh Bhojanapalli, 2020, ICML.

Robust, Deep and Inductive Anomaly Detection pdf

Sanjay Chawla, Aditya Krishna Menon, Raghavendra Chalapathy, 2017, ECML/PKDD.

Distilling Double Descent pdf

Ankit Singh Rawat, Harikrishna Narasimhan, Sashank J. Reddi, 2021, ArXiv.

Beam search algorithms for multilabel learning

C. Elkan, A. Menon, Shankar Vembu, 2013, Machine Learning.

The risk of trivial solutions in bipartite top ranking

Aditya Krishna Menon, A. Menon, 2018, Machine Learning.

Learning from Binary Labels with Instance-Dependent Corruption pdf

Nagarajan Natarajan, Aditya Krishna Menon, Brendan van Rooyen, 2016, ArXiv.

Making Neural Networks Robust to Label Noise: a Loss Correction Approach pdf

Richard Nock, Alessandro Rozza, Lizhen Qu, 2016, ArXiv.

An Average Classification Algorithm pdf

Aditya Krishna Menon, Brendan van Rooyen, A. Menon, 2015, ArXiv.

The cost of fairness in classification pdf

Aditya Krishna Menon, Robert C. Williamson, R. C. Williamson, 2017, ArXiv.

On the Reproducibility of Neural Network Predictions pdf

Ankit Singh Rawat, Andreas Veit, Srinadh Bhojanapalli, 2021, ArXiv.

Response prediction using collaborative filtering with hierarchies and side-information

Sachin Garg, Deepak Agarwal, Aditya Krishna Menon, 2011, KDD.

Comparative Document Summarisation via Classification

A. Menon, Lexing Xie, A. Mathews, 2018, AAAI.

Structured Recommendation pdf

Cheng Soon Ong, Dawei Chen, Lexing Xie, 2017, ArXiv.

Semantic Label Smoothing for Sequence to Sequence Problems

Sanjiv Kumar, Aditya Krishna Menon, Seungyeon Kim, 2020, EMNLP.

Doubly Optimized Calibrated Support Vector Machine (DOC-SVM): An Algorithm for Joint Optimization of Discrimination and Calibration

Xiaoqian Jiang, Lucila Ohno-Machado, Aditya Menon, 2012, PloS one.

Low-Rank Linear Cold-Start Recommendation from Social Data

Scott Sanner, Lexing Xie, Aditya Krishna Menon, 2017, AAAI.

When Does Confidence-Based Cascade Deferral Suffice?

Wittawat Jitkrittum, A. Menon, A. Rawat, 2023, NeurIPS.

Monge beats Bayes: Hardness Results for Adversarial Training pdf

Richard Nock, Cheng Soon Ong, Aditya Krishna Menon, 2018, ICML.

EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval

R. Fergus, M. Zaheer, Wittawat Jitkrittum, 2023, ArXiv.

On student-teacher deviations in distillation: does it pay to disobey?

Srinadh Bhojanapalli, A. Menon, H. Mobahi, 2023, arXiv.org.

Supervision Complexity and its Role in Knowledge Distillation

A. Menon, A. Rawat, Seungyeon Kim, 2023, ICLR.

Self-supervised Learning for Deep Models in Recommendations pdf

Jieqi Kang, Ed H. Chi, Xinyang Yi, 2020, ArXiv.

Learning and Inference in Probabilistic Classifier Chains with Beam Search

Charles Elkan, Shankar Vembu, Aditya Krishna Menon, 2012, ECML/PKDD.

Complementary-Label Learning for Arbitrary Losses and Models

Gang Niu, Masashi Sugiyama, Takashi Ishida, 2018, ICML.

On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data

Masashi Sugiyama, A. Menon, Gang Niu, 2018, ICLR.

A colorful approach to text processing by example

Butler W. Lampson, Sumit Gulwani, Adam Tauman Kalai, 2013, UIST.

A Machine Learning Framework for Programming by Example

Butler W. Lampson, Sumit Gulwani, Adam Tauman Kalai, 2013, ICML.

Textual Features for Programming by Example pdf

Butler W. Lampson, Sumit Gulwani, Adam Tauman Kalai, 2012, ArXiv.

A scaled Bregman theorem with applications

Richard Nock, Cheng Soon Ong, Aditya Krishna Menon, 2016, NIPS.

Detecting inappropriate access to electronic health records using collaborative filtering

Jihoon Kim, Xiaoqian Jiang, Lucila Ohno-Machado, 2014, Machine Learning.

ResMem: Learn what you can and memorize the rest

M. Zaheer, A. Menon, A. Rawat, 2023, arXiv.org.

PathRec: Visual Analysis of Travel Route Recommendations

Dongwoo Kim, Cheng Soon Ong, John Grundy, 2017, RecSys.

Cold-start playlist recommendation with multitask learning pdf

Cheng Soon Ong, Dawei Chen, Aditya Krishna Menon, 2018, PeerJ Prepr..

When in Doubt, Summon the Titans: Efficient Inference with Large Models pdf

Ankit Singh Rawat, Amr Ahmed, Manzil Zaheer, 2021, ArXiv.

The importance of feature preprocessing for differentially private linear optimization

A. Suresh, A. Menon, Ziteng Sun, 2023, ICLR.

Fast Algorithms for Approximating the Singular Value Decomposition

Charles Elkan, Aditya Krishna Menon, C. Elkan, 2011, TKDD.

On the Effectiveness of Linear Models for One-Class Collaborative Filtering

Scott Sanner, Aditya Krishna Menon, Suvash Sedhain, 2016, AAAI.

An incremental data-stream sketch using sparse random projections

Sanjay Chawla, Anastasios Viglas, Aditya Krishna Menon, 2007, SDM.

Random projections and applications to dimensionality reduction

Aditya Krishna Menon, A. Menon, 2007 .

On student-teacher deviations in distillation: does it pay to disobey?

Srinadh Bhojanapalli, A. Menon, H. Mobahi, 2023, NeurIPS.

Post-hoc estimators for learning to defer to an expert

Wittawat Jitkrittum, A. Menon, A. Rawat, 2022, NeurIPS.

Learning from binary labels with instance-dependent noise

Brendan van Rooyen, A. Menon, Nagarajan Natarajan, 2018, Machine Learning.

Plugin estimators for selective classification with out-of-distribution detection

Wittawat Jitkrittum, A. Menon, Surinder Kumar, 2023, 2301.12386.

What do larger image classifiers memorise?

A. Menon, A. Rawat, Vaishnavh Nagarajan, 2023, 2310.05337.

Think before you speak: Training Language Models With Pause Tokens

A. Menon, A. Rawat, Vaishnavh Nagarajan, 2023, ArXiv.

Self-supervised Learning for Large-scale Item Recommendations

Ed H. Chi, Felix X. Yu, Lichan Hong, 2020, CIKM.

Language Model Cascades: Token-level uncertainty and beyond

Wittawat Jitkrittum, A. Menon, A. Rawat, 2024, ArXiv.

DistillSpec: Improving Speculative Decoding via Knowledge Distillation

Afshin Rostamizadeh, A. Menon, A. Rawat, 2023, ArXiv.