Talwalkar, Ameet

70 publications

TMLR 2025 Agreement-Based Cascading for Efficient Inference Steven Kolawole, Don Dennis, Ameet Talwalkar, Virginia Smith

ICML 2025 Copilot Arena: A Platform for Code LLM Evaluation in the Wild Wayne Chi, Valerie Chen, Anastasios Nikolas Angelopoulos, Wei-Lin Chiang, Aditya Mittal, Naman Jain, Tianjun Zhang, Ion Stoica, Chris Donahue, Ameet Talwalkar

TMLR 2025 L2G: Repurposing Language Models for Genomics Tasks Wenduo Cheng, Junhong Shen, Mikhail Khodak, Jian Ma, Ameet Talwalkar

AAAI 2025 Learning Personalized Decision Support Policies Umang Bhatt, Valerie Chen, Katherine M. Collins, Parameswaran Kamalaruban, Emma Kallina, Adrian Weller, Ameet Talwalkar

ICLR 2025 Specialized Foundation Models Struggle to Beat Supervised Baselines Zongzhe Xu, Ritvik Gupta, Wenduo Cheng, Alexander Shen, Junhong Shen, Ameet Talwalkar, Mikhail Khodak

TMLR 2025 The RealHumanEval: Evaluating Large Language Models’ Abilities to Support Programmers Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David Sontag

NeurIPS 2025 Thinking vs. Doing: Improving Agent Reasoning by Scaling Test-Time Interaction Junhong Shen, Hao Bai, Lunjun Zhang, Yifei Zhou, Amrith Setlur, Shengbang Tong, Diego Caples, Nan Jiang, Tong Zhang, Ameet Talwalkar, Aviral Kumar

NeurIPS 2025 This Time Is Different: An Observability Perspective on Time Series Foundation Models Ben Cohen, Emaad Khwaja, Youssef Doubli, Salahidine Lemaachi, Chris Lettieri, Charles Masson, Hugo Miccinilli, Elise Ramé, Qiqi Ren, Afshin Rostamizadeh, Jean Ogier du Terrail, Anna-Monica Toon, Kan Wang, Stephan Xie, Zongzhe Xu, Viktoriya Zhukova, David Asker, Ameet Talwalkar, Othmane Abou-Amal

ICLR 2025 Understanding Optimization in Deep Learning with Central Flows Jeremy Cohen, Alex Damian, Ameet Talwalkar, J Zico Kolter, Jason D. Lee

ICLRW 2025 WorkflowAgent: Towards Specialized Web Agents Using Production-Scale Workflow Data Junhong Shen, Atishay Jain, Zedian Xiao, Ishan Amlekar, Mouad Hadji, Aaron Podolny, Ameet Talwalkar

ICLR 2024 Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances Mikhail Khodak, Edmond Chow, Maria Florina Balcan, Ameet Talwalkar

NeurIPSW 2024 Modulating Language Model Experiences Through Frictions Katherine M. Collins, Valerie Chen, Ilia Sucholutsky, Hannah Rose Kirk, Malak Sadek, Holli Sargeant, Ameet Talwalkar, Adrian Weller, Umang Bhatt

TMLR 2024 Multitask Learning Can Improve Worst-Group Outcomes Atharva Kulkarni, Lucio M. Dery, Amrith Setlur, Aditi Raghunathan, Ameet Talwalkar, Graham Neubig

AAAI 2024 On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods Kasun Amarasinghe, Kit T. Rodolfa, Sérgio M. Jesus, Valerie Chen, Vladimir Balayan, Pedro Saleiro, Pedro Bizarro, Ameet Talwalkar, Rayid Ghani

ICMLW 2024 Revisiting Cascaded Ensembles for Efficient Inference Steven Kolawole, Don Dennis, Ameet Talwalkar, Virginia Smith

NeurIPSW 2024 Specialized Foundation Models Struggle to Beat Supervised Baselines Zongzhe Xu, Ritvik Gupta, Wenduo Cheng, Alexander Shen, Junhong Shen, Ameet Talwalkar, Mikhail Khodak

NeurIPSW 2024 The Impact of Element Ordering on LM Agent Performance Wayne Chi, Ameet Talwalkar, Chris Donahue

TMLR 2024 UPS: Efficiently Building Foundation Models for PDE Solving via Cross-Modal Adaptation Junhong Shen, Tanya Marwah, Ameet Talwalkar

ICMLW 2024 UPS: Efficiently Building Foundation Models for PDE Solving via Cross-Modal Adaptation Junhong Shen, Tanya Marwah, Ameet Talwalkar

ICLR 2023 AANG : Automating Auxiliary Learning Lucio M. Dery, Paul Michel, Mikhail Khodak, Graham Neubig, Ameet Talwalkar

TMLR 2023 Assisting Human Decisions in Document Matching Joon Sik Kim, Valerie Chen, Danish Pruthi, Nihar B Shah, Ameet Talwalkar

ICML 2023 Cross-Modal Fine-Tuning: Align Then Refine Junhong Shen, Liam Li, Lucio M. Dery, Corey Staten, Mikhail Khodak, Graham Neubig, Ameet Talwalkar

NeurIPSW 2023 Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances Mikhail Khodak, Edmond Chow, Maria Florina Balcan, Ameet Talwalkar

NeurIPSW 2023 Simulating Iterative Human-AI Interaction in Programming with LLMs Hussein Mozannar, Valerie Chen, Dennis Wei, Prasanna Sattigeri, Manish Nagireddy, Subhro Das, Ameet Talwalkar, David Sontag

TMLR 2023 Towards a More Rigorous Science of Blindspot Discovery in Image Classification Models Gregory Plumb, Nari Johnson, Angel Cabrera, Ameet Talwalkar

NeurIPS 2022 Bayesian Persuasion for Algorithmic Recourse Keegan Harris, Valerie Chen, Joon Kim, Ameet Talwalkar, Hoda Heidari, Steven Z. Wu

NeurIPS 2022 Efficient Architecture Search for Diverse Tasks Junhong Shen, Misha Khodak, Ameet Talwalkar

ICMLW 2022 Evaluating Systemic Error Detection Methods Using Synthetic Images Gregory Plumb, Nari Johnson, Ángel Cabrera, Marco Tulio Ribeiro, Ameet Talwalkar

TMLR 2022 Finding and Fixing Spurious Patterns with Explanations Gregory Plumb, Marco Tulio Ribeiro, Ameet Talwalkar

NeurIPS 2022 Learning Predictions for Algorithms with Predictions Misha Khodak, Maria-Florina F Balcan, Ameet Talwalkar, Sergei Vassilvitskii

NeurIPS 2022 NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks Renbo Tu, Nicholas Roberts, Misha Khodak, Junhong Shen, Frederic Sala, Ameet Talwalkar

NeurIPS 2022 Provably Tuning the ElasticNet Across Instances Maria-Florina F Balcan, Misha Khodak, Dravyansh Sharma, Ameet Talwalkar

ICML 2022 Sanity Simulations for Saliency Methods Joon Sik Kim, Gregory Plumb, Ameet Talwalkar

ICLR 2022 Should We Be Pre-Training? an Argument for End-Task Aware Training as an Alternative Lucio M. Dery, Paul Michel, Ameet Talwalkar, Graham Neubig

NeurIPS 2022 Use-Case-Grounded Simulations for Explanation Evaluation Valerie Chen, Nari Johnson, Nicholay Topin, Gregory Plumb, Ameet Talwalkar

AISTATS 2021 On Data Efficiency of Meta-Learning Maruan Al-Shedivat, Liam Li, Eric Xing, Ameet Talwalkar

ICLR 2021 A Learning Theoretic Perspective on Local Explainability Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar

NeurIPS 2021 Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina F Balcan, Virginia Smith, Ameet Talwalkar

ICLR 2021 Geometry-Aware Gradient Algorithms for Neural Architecture Search Liam Li, Mikhail Khodak, Nina Balcan, Ameet Talwalkar

ICLR 2021 Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability Jeremy Cohen, Simran Kaur, Yuanzhi Li, J Zico Kolter, Ameet Talwalkar

NeurIPS 2021 Learning-to-Learn Non-Convex Piecewise-Lipschitz Functions Maria-Florina F Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar

NeurIPS 2021 Rethinking Neural Operations for Diverse Tasks Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar

NeurIPSW 2021 Simulated User Studies for Explanation Evaluation Valerie Chen, Gregory Plumb, Nicholay Topin, Ameet Talwalkar

ICLR 2020 Differentially Private Meta-Learning Jeffrey Li, Mikhail Khodak, Sebastian Caldas, Ameet Talwalkar

ICML 2020 Explaining Groups of Points in Low-Dimensional Representations Gregory Plumb, Jonathan Terhorst, Sriram Sankararaman, Ameet Talwalkar

ICML 2020 FACT: A Diagnostic for Group Fairness Trade-Offs Joon Sik Kim, Jiahao Chen, Ameet Talwalkar

AISTATS 2020 Learning Fair Representations for Kernel Models Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar

NeurIPS 2020 Regularizing Black-Box Models for Improved Interpretability Gregory Plumb, Maruan Al-Shedivat, Ángel Alexander Cabrera, Adam Perer, Eric P. Xing, Ameet Talwalkar

ICMLW 2019 Federated Optimization for Heterogeneous Networks Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith

ICML 2019 Provable Guarantees for Gradient-Based Meta-Learning Maria-Florina Balcan, Mikhail Khodak, Ameet Talwalkar

UAI 2019 Random Search and Reproducibility for Neural Architecture Search Liam Li, Ameet Talwalkar

ICLR 2017 Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization Lisha Li, Kevin G. Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar

ICLR 2017 Paleo: A Performance Model for Deep Neural Networks Hang Qi, Evan Randall Sparks, Ameet Talwalkar

MLOSS 2016 MLlib: Machine Learning in Apache Spark Xiangrui Meng, Joseph Bradley, Burak Yavuz, Evan Sparks, Shivaram Venkataraman, Davies Liu, Jeremy Freeman, Db Tsai, Manish Amde, Sean Owen, Doris Xin, Reynold Xin, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar

AISTATS 2016 Non-Stochastic Best Arm Identification and Hyperparameter Optimization Kevin G. Jamieson, Ameet Talwalkar

AISTATS 2016 Supervised Neighborhoods for Distributed Nonparametric Regression Adam E. Bloniarz, Ameet Talwalkar, Bin Yu, Christopher Wu

JMLR 2015 Distributed Matrix Completion and Robust Factorization Lester Mackey, Ameet Talwalkar, Michael I. Jordan

ICCV 2013 Distributed Low-Rank Subspace Segmentation Ameet Talwalkar, Lester Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan

JMLR 2013 Large-Scale SVD and Manifold Learning Ameet Talwalkar, Sanjiv Kumar, Mehryar Mohri, Henry Rowley

JMLR 2012 Sampling Methods for the Nystr M Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

ICML 2012 The Big Data Bootstrap Ariel Kleiner, Ameet Talwalkar, Purnamrita Sarkar, Michael I. Jordan

AISTATS 2011 Can Matrix Coherence Be Efficiently and Accurately Estimated? Mehryar Mohri, Ameet Talwalkar

NeurIPS 2011 Divide-and-Conquer Matrix Factorization Lester W. Mackey, Michael I. Jordan, Ameet Talwalkar

UAI 2010 Matrix Coherence and the Nystrom Method Ameet Talwalkar, Afshin Rostamizadeh

AISTATS 2010 On the Impact of Kernel Approximation on Learning Accuracy Corinna Cortes, Mehryar Mohri, Ameet Talwalkar

NeurIPS 2009 Ensemble Nystrom Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

ICML 2009 On Sampling-Based Approximate Spectral Decomposition Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

AISTATS 2009 Sampling Techniques for the Nystrom Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

CVPR 2008 Large-Scale Manifold Learning Ameet Talwalkar, Sanjiv Kumar, Henry A. Rowley

ICML 2008 Sequence Kernels for Predicting Protein Essentiality Cyril Allauzen, Mehryar Mohri, Ameet Talwalkar