Pranjal Awasthi

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Limitations of Local Filters of Lipschitz and Monotone Functions

Sofya Raskhodnikova, Marco Molinaro, Pranjal Awasthi, 2015, TOCT.

Learning Mixtures of Ranking Models

Avrim Blum, Aravindan Vijayaraghavan, Pranjal Awasthi, 2014, NIPS.

Center Based Clustering: A Foundational Perspective

Maria-Florina Balcan, Pranjal Awasthi, Maria-Florina Balcan, 2014 .

Online Stochastic Optimization in the Large: Application to Kidney Exchange

Tuomas Sandholm, Pranjal Awasthi, Pranjal Awasthi, 2009, IJCAI.

On Nash-Equilibria of Approximation-Stable Games

Santosh S. Vempala, Maria-Florina Balcan, Avrim Blum, 2010, SAGT.

Learning and 1-bit Compressed Sensing under Asymmetric Noise

Maria-Florina Balcan, Pranjal Awasthi, Hongyang Zhang, 2016, COLT.

Testing Lipschitz Functions on Hypergrid Domains

Sofya Raskhodnikova, Marco Molinaro, Pranjal Awasthi, 2012, Algorithmica.

Improved Guarantees for Agnostic Learning of Disjunctions

Avrim Blum, Pranjal Awasthi, Or Sheffet, 2010, COLT.

PAC-Bayes Learning Bounds for Sample-Dependent Priors

Pranjal Awasthi, Satyen Kale, Mehryar Mohri, 2020, NeurIPS.

Clustering Under Stability Assumptions

Pranjal Awasthi, 2016, Encyclopedia of Algorithms.

Efficient active learning of sparse halfspaces with arbitrary bounded noise pdf

Jie Shen, Pranjal Awasthi, Chicheng Zhang, 2020, NeurIPS.

Limitations of Local Filters of Lipschitz and Monotone Functions

Sofya Raskhodnikova, Marco Molinaro, Pranjal Awasthi, 2015, TOCT.

Adversarially Robust Low Dimensional Representations pdf

Aravindan Vijayaraghavan, Pranjal Awasthi, Vaggos Chatziafratis, 2019, COLT.

Local algorithms for interactive clustering

Maria-Florina Balcan, Pranjal Awasthi, Konstantin Voevodski, 2013, ICML.

Part Of Speech Tagging and Chunking with HMM and CRF

Balaraman Ravindran, Pranjal Awasthi, Delip Rao, 2006 .

Decision trees for entity identification: approximation algorithms and hardness results

Mukesh K. Mohania, Sambuddha Roy, Venkatesan T. Chakaravarthy, 2007, PODS '07.

Additive Approximation for Near-Perfect Phylogeny Construction pdf

Avrim Blum, Pranjal Awasthi, Or Sheffet, 2012, APPROX-RANDOM.

On some provably correct cases of variational inference for topic models

Andrej Risteski, Pranjal Awasthi, Pranjal Awasthi, 2015, NIPS.

Estimating Principal Components under Adversarial Perturbations

Xue Chen, Aravindan Vijayaraghavan, Pranjal Awasthi, 2020, COLT.

General and Robust Communication-Efficient Algorithms for Distributed Clustering pdf

Maria-Florina Balcan, Pranjal Awasthi, Colin White, 2017, ArXiv.

Crowdsourcing with Arbitrary Adversaries

Pranjal Awasthi, Matthäus Kleindessner, Pranjal Awasthi, 2018, ICML.

Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks

Pranjal Awasthi, Mehryar Mohri, Natalie Frank, 2020, ICML.

Center-based clustering under perturbation stability

Avrim Blum, Pranjal Awasthi, Or Sheffet, 2010, Inf. Process. Lett..

Beyond Individual and Group Fairness pdf

Yishay Mansour, Corinna Cortes, Pranjal Awasthi, 2020, ArXiv.

Image Modeling Using Tree Structured Conditional Random Fields

Balaraman Ravindran, Pranjal Awasthi, Aakanksha Gagrani, 2007, IJCAI.

Adversarial robustness via robust low rank representations pdf

Ankit Singh Rawat, Aravindan Vijayaraghavan, Pranjal Awasthi, 2020, NeurIPS.

On Robustness to Adversarial Examples and Polynomial Optimization

Aravindan Vijayaraghavan, Pranjal Awasthi, Abhratanu Dutta, 2019, NeurIPS.

Clustering Under Natural Stability Assumptions

Avrim Blum, Pranjal Awasthi, Or Sheffet, 2010 .

Spectral Embedding of k-Cliques, Graph Partitioning and k-Means

Ravishankar Krishnaswamy, Moses Charikar, Pranjal Awasthi, 2016, ITCS.

Label optimal regret bounds for online local learning pdf

Kevin A. Lai, Andrej Risteski, Moses Charikar, 2015, COLT.

Adversarial Robustness Across Representation Spaces pdf

Andrew Tomkins, Pranjal Awasthi, Chun-Sung Ferng, 2020, ArXiv.

Testing Lipschitz Functions on Hypergrid Domains

Sofya Raskhodnikova, Marco Molinaro, Pranjal Awasthi, 2012, Algorithmica.

Learning using Local Membership Queries under Smooth Distributions pdf

Varun Kanade, Pranjal Awasthi, Varun Kanade, 2012, ArXiv.

On the adaptivity gap in two-stage robust linear optimization under uncertain packing constraints

Pranjal Awasthi, Vineet Goyal, Brian Y. Lu, 2019, Math. Program..

Equalized odds postprocessing under imperfect group information

Pranjal Awasthi, Jamie Morgenstern, Matthaus Kleindessner, 2019, AISTATS.

A Deep Conditioning Treatment of Neural Networks pdf

Pranjal Awasthi, Naman Agarwal, Satyen Kale, 2020, ALT.

On the Rademacher Complexity of Linear Hypothesis Sets pdf

Pranjal Awasthi, Mehryar Mohri, Natalie Frank, 2020, ArXiv.

The Power of Localization for Efficiently Learning Linear Separators with Malicious Noise pdf

Maria-Florina Balcan, Philip M. Long, Pranjal Awasthi, 2013, ArXiv.

Towards Learning Sparsely Used Dictionaries with Arbitrary Supports

Aravindan Vijayaraghavan, Pranjal Awasthi, Aravindan Vijayaraghavan, 2018, 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS).

Approximation Algorithms and New Models for Clustering and Learning

Pranjal Awasthi, Pranjal Awasthi, 2013 .

Efficient Learning of Linear Separators under Bounded Noise

Maria-Florina Balcan, Ruth Urner, Pranjal Awasthi, 2015, COLT.

Supervised Clustering

Pranjal Awasthi, Reza Bosagh Zadeh, R. Zadeh, 2010, NIPS.

Relax, No Need to Round: Integrality of Clustering Formulations

Ravishankar Krishnaswamy, Rachel Ward, Moses Charikar, 2014, ITCS.

The Power of Localization for Efficiently Learning Linear Separators with Noise

Maria-Florina Balcan, Philip M. Long, Pranjal Awasthi, 2013, J. ACM.

Stability Yields a PTAS for k-Median and k-Means Clustering

Avrim Blum, Pranjal Awasthi, Or Sheffet, 2010, 2010 IEEE 51st Annual Symposium on Foundations of Computer Science.

The power of localization for efficiently learning linear separators with noise

Maria-Florina Balcan, Philip M. Long, Pranjal Awasthi, 2014, STOC.

Clustering Semi-Random Mixtures of Gaussians

Aravindan Vijayaraghavan, Pranjal Awasthi, Aravindan Vijayaraghavan, 2017, ICML.

Bilu-Linial stability, certified algorithms and the Independent Set problem

Avrim Blum, Chen Dan, Pranjal Awasthi, 2018, ESA.

Learning Using Local Membership Queries

Varun Kanade, Vitaly Feldman, Pranjal Awasthi, 2012, COLT.

A case for Data Democratization

Pranjal Awasthi, Jordana J. George, Jordana J. George, 2020, AMCIS.

The Hardness of Approximation of Euclidean k-Means

Ravishankar Krishnaswamy, Moses Charikar, Pranjal Awasthi, 2015, SoCG.

A Notion of Individual Fairness for Clustering pdf

Pranjal Awasthi, Jamie Morgenstern, Matthaus Kleindessner, 2020, ArXiv.

Robust vertex enumeration for convex hulls in high dimensions

Bahman Kalantari, Pranjal Awasthi, Yikai Zhang, 2018, AISTATS.

Fair k-Center Clustering for Data Summarization

Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, 2019, ICML.

Guarantees for Spectral Clustering with Fairness Constraints

Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, 2019, ICML.

Adaptive Sampling to Reduce Disparate Performance pdf

Jacob Abernethy, Jie Zhang, Pranjal Awasthi, 2020, ArXiv.

Robust Matrix Completion from Quantized Observations

Ping Li, Pranjal Awasthi, Jie Shen, 2019, AISTATS.

Efficient PAC Learning from the Crowd

Yishay Mansour, Avrim Blum, Pranjal Awasthi, 2017, COLT.

Robust Communication-Optimal Distributed Clustering Algorithms

David P. Woodruff, Maria-Florina Balcan, Ainesh Bakshi, 2017, ICALP.

Improved Spectral-Norm Bounds for Clustering

Pranjal Awasthi, Or Sheffet, Pranjal Awasthi, 2012, APPROX-RANDOM.

Calibration and Consistency of Adversarial Surrogate Losses pdf

Mehryar Mohri, Pranjal Awasthi, Natalie Frank, 2021, NeurIPS.

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

Mehryar Mohri, Pranjal Awasthi, Natalie S. Frank, 2021, NeurIPS.

Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information

Pranjal Awasthi, Jamie Morgenstern, Alex Beutel, 2021, FAccT.

Semi-supervised Active Regression pdf

Pranjal Awasthi, Nived Rajaraman, Fnu Devvrit, 2021, ArXiv.

A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness pdf

Jacob Abernethy, Pranjal Awasthi, Satyen Kale, 2021, ArXiv.

Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective

Ed H. Chi, Pranjal Awasthi, Alex Beutel, 2021, AIES.

Adversarially Robust Low Dimensional Representations

Aravindan Vijayaraghavan, Pranjal Awasthi, Vaggos Chatziafratis, 2021, COLT.

A Finer Calibration Analysis for Adversarial Robustness pdf

Mehryar Mohri, Pranjal Awasthi, Anqi Mao, 2021, ArXiv.

On the benefits of maximum likelihood estimation for Regression and Forecasting pdf

Abhimanyu Das, Pranjal Awasthi, Ananda Theertha Suresh, 2021, ICLR.

Neural Active Learning with Performance Guarantees pdf

Claudio Gentile, Pranjal Awasthi, Christoph Dann, 2021, NeurIPS.

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

Aravindan Vijayaraghavan, Pranjal Awasthi, Alex Tang, 2021, Neural Information Processing Systems.