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Publication search results
found 96 matches
- 2024
- Nika Haghtalab
, Tim Roughgarden, Abhishek Shetty:
Smoothed Analysis with Adaptive Adversaries. J. ACM 71(3): 19 (2024) - Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, Ellen Vitercik:
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. SIGecom Exch. 22(1): 74-82 (2024) - Nivasini Ananthakrishnan, Stephen Bates, Michael I. Jordan, Nika Haghtalab:
Delegating Data Collection in Decentralized Machine Learning. AISTATS 2024: 478-486 - Jessica Dai, Bailey Flanigan, Meena Jagadeesan, Nika Haghtalab, Chara Podimata:
Can Probabilistic Feedback Drive User Impacts in Online Platforms? AISTATS 2024: 2512-2520 - Danny Halawi, Alexander Wei, Eric Wallace, Tony Tong Wang, Nika Haghtalab, Jacob Steinhardt:
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. ICML 2024 - Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty:
Smooth Nash Equilibria: Algorithms and Complexity. ITCS 2024: 37:1-37:22 - Nika Haghtalab, Nicole Immorlica, Brendan Lucier, Markus Mobius, Divyarthi Mohan:
Communicating with Anecdotes (Extended Abstract). ITCS 2024: 57:1-57:2 - Jessica Dai, Bailey Flanigan, Nika Haghtalab, Meena Jagadeesan, Chara Podimata:
Can Probabilistic Feedback Drive User Impacts in Online Platforms? CoRR abs/2401.05304 (2024) - Nika Haghtalab, Mingda Qiao, Kunhe Yang:
Platforms for Efficient and Incentive-Aware Collaboration. CoRR abs/2402.15169 (2024) - Danny Halawi, Alexander Wei, Eric Wallace, Tony T. Wang, Nika Haghtalab, Jacob Steinhardt:
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. CoRR abs/2406.20053 (2024) - Nika Haghtalab, Mingda Qiao, Kunhe Yang, Eric Zhao:
Truthfulness of Calibration Measures. CoRR abs/2407.13979 (2024) - Nivasini Ananthakrishnan, Nika Haghtalab, Chara Podimata, Kunhe Yang:
Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interaction. CoRR abs/2408.08272 (2024) - Emilio Calvano, Nika Haghtalab, Ellen Vitercik, Eric Zhao:
Algorithmic Content Selection and the Impact of User Disengagement. CoRR abs/2410.13108 (2024) - Jessica Dai, Nika Haghtalab, Eric Zhao:
Learning With Multi-Group Guarantees For Clusterable Subpopulations. CoRR abs/2410.14588 (2024) - 2023
- Meena Jagadeesan, Michael I. Jordan, Nika Haghtalab:
Competition, Alignment, and Equilibria in Digital Marketplaces. AAAI 2023: 5689-5696 - Pranjal Awasthi, Nika Haghtalab, Eric Zhao:
Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes. COLT 2023: 5943-5949 - Alexander Wei, Nika Haghtalab, Jacob Steinhardt:
Jailbroken: How Does LLM Safety Training Fail? NeurIPS 2023 - Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty:
Smoothed Analysis of Sequential Probability Assignment. NeurIPS 2023 - Nika Haghtalab, Michael I. Jordan, Eric Zhao:
A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning. NeurIPS 2023 - Nika Haghtalab, Chara Podimata, Kunhe Yang:
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents. NeurIPS 2023 - Meena Jagadeesan, Michael I. Jordan, Jacob Steinhardt, Nika Haghtalab:
Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition. NeurIPS 2023 - Naveen Durvasula, Nika Haghtalab, Manolis Zampetakis:
Smoothed Analysis of Online Non-parametric Auctions. EC 2023: 540-560 - Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, Ellen Vitercik:
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. EC 2023: 816 - Mahsa Derakhshan, Naveen Durvasula, Nika Haghtalab:
Stochastic Minimum Vertex Cover in General Graphs: A 3/2-Approximation. STOC 2023: 242-253 - Mahsa Derakhshan, Naveen Durvasula, Nika Haghtalab:
Stochastic Minimum Vertex Cover in General Graphs: a 3/2-Approximation. CoRR abs/2302.02567 (2023) - Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, Ellen Vitercik:
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. CoRR abs/2302.09700 (2023) - Nika Haghtalab, Michael I. Jordan, Eric Zhao:
A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning. CoRR abs/2302.10863 (2023) - Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty:
Smoothed Analysis of Sequential Probability Assignment. CoRR abs/2303.04845 (2023) - Nika Haghtalab, Chara Podimata, Kunhe Yang:
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents. CoRR abs/2306.02704 (2023) - Meena Jagadeesan, Michael I. Jordan, Jacob Steinhardt, Nika Haghtalab:
Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition. CoRR abs/2306.14670 (2023)
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