Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Pranjal Awasthi

Do More Negative Samples Necessarily Hurt in Contrastive Learning?


May 03, 2022
Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath

* 16 pages 

  Access Paper or Ask Questions

Distributionally Robust Data Join


Feb 11, 2022
Pranjal Awasthi, Christopher Jung, Jamie Morgenstern


  Access Paper or Ask Questions

Agnostic Learnability of Halfspaces via Logistic Loss


Jan 31, 2022
Ziwei Ji, Kwangjun Ahn, Pranjal Awasthi, Satyen Kale, Stefani Karp


  Access Paper or Ask Questions

On the Existence of the Adversarial Bayes Classifier (Extended Version)


Dec 03, 2021
Pranjal Awasthi, Natalie S. Frank, Mehryar Mohri

* 49 pages, 8 figures. Extended version of the paper "On the Existence of the Adversarial Bayes Classifier" published in NeurIPS 

  Access Paper or Ask Questions

Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations


Aug 01, 2021
Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

* 45 pages (including appendix). This version fixes an error in the previous version of the paper 

  Access Paper or Ask Questions

On the benefits of maximum likelihood estimation for Regression and Forecasting


Jun 18, 2021
Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh


  Access Paper or Ask Questions

Semi-supervised Active Regression


Jun 12, 2021
Fnu Devvrit, Nived Rajaraman, Pranjal Awasthi


  Access Paper or Ask Questions

Neural Active Learning with Performance Guarantees


Jun 06, 2021
Pranjal Awasthi, Christoph Dann, Claudio Gentile, Ayush Sekhari, Zhilei Wang

* 30 pages 

  Access Paper or Ask Questions

Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective


May 20, 2021
Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel


  Access Paper or Ask Questions

A Finer Calibration Analysis for Adversarial Robustness


May 06, 2021
Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

* arXiv admin note: text overlap with arXiv:2104.09658 

  Access Paper or Ask Questions

Calibration and Consistency of Adversarial Surrogate Losses


May 04, 2021
Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong


  Access Paper or Ask Questions

A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness


Mar 03, 2021
Jacob Abernethy, Pranjal Awasthi, Satyen Kale

* Fixed misspelled first author name 

  Access Paper or Ask Questions

Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information


Feb 16, 2021
Pranjal Awasthi, Alex Beutel, Matthaeus Kleindessner, Jamie Morgenstern, Xuezhi Wang


  Access Paper or Ask Questions

Adversarial Robustness Across Representation Spaces


Dec 01, 2020
Pranjal Awasthi, George Yu, Chun-Sung Ferng, Andrew Tomkins, Da-Cheng Juan


  Access Paper or Ask Questions

Beyond Individual and Group Fairness


Aug 21, 2020
Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri


  Access Paper or Ask Questions

Adversarial robustness via robust low rank representations


Aug 01, 2020
Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan

* fixed a bug in the proof of Proposition B.2 

  Access Paper or Ask Questions

On the Rademacher Complexity of Linear Hypothesis Sets


Jul 21, 2020
Pranjal Awasthi, Natalie Frank, Mehryar Mohri


  Access Paper or Ask Questions

Adaptive Sampling to Reduce Disparate Performance


Jun 11, 2020
Jacob Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Jie Zhang


  Access Paper or Ask Questions

A Notion of Individual Fairness for Clustering


Jun 08, 2020
Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern


  Access Paper or Ask Questions

Estimating Principal Components under Adversarial Perturbations


Jun 02, 2020
Pranjal Awasthi, Xue Chen, Aravindan Vijayaraghavan

* It is to appear at COLT 2020 

  Access Paper or Ask Questions

Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks


Apr 28, 2020
Pranjal Awasthi, Natalie Frank, Mehryar Mohri


  Access Paper or Ask Questions

Efficient active learning of sparse halfspaces with arbitrary bounded noise


Feb 12, 2020
Chicheng Zhang, Jie Shen, Pranjal Awasthi

* 43 pages, 2 figures 

  Access Paper or Ask Questions

A Deep Conditioning Treatment of Neural Networks


Feb 04, 2020
Naman Agarwal, Pranjal Awasthi, Satyen Kale


  Access Paper or Ask Questions

Adversarially Robust Low Dimensional Representations


Nov 29, 2019
Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan

* 68 pages including references 

  Access Paper or Ask Questions

On Robustness to Adversarial Examples and Polynomial Optimization


Nov 12, 2019
Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan

* To appear at NeurIPS2019. 30 pages 

  Access Paper or Ask Questions

Effectiveness of Equalized Odds for Fair Classification under Imperfect Group Information


Jun 07, 2019
Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern


  Access Paper or Ask Questions