Nika Haghtalab
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
29
Venues
12
Active years
2014–2026
Best venue rank
A*
Where they publish
Papers
29 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | COLT | Blackwell Approachability and Gradient Equilibrium are Equivalent. | Brian W. Lee, Nika Haghtalab, Michael I. Jordan, Ryan J. Tibshirani |
| 2025 | COLT | Conference on Learning Theory 2025: Preface. | Nika Haghtalab, Ankur Moitra |
| 2025 | ICML | Learning With Multi-Group Guarantees For Clusterable Subpopulations. | Jessica Dai, Nika Haghtalab, Eric Zhao |
| 2025 | SODA | Platforms for Efficient and Incentive-Aware Collaboration. | Nika Haghtalab, Mingda Qiao, Kunhe Yang |
| 2024 | AISTATS | Delegating Data Collection in Decentralized Machine Learning. | Nivasini Ananthakrishnan, Stephen Bates, Michael I. Jordan, Nika Haghtalab |
| 2024 | AISTATS | Can Probabilistic Feedback Drive User Impacts in Online Platforms? | Jessica Dai, Bailey Flanigan, Meena Jagadeesan, Nika Haghtalab, Chara Podimata |
| 2024 | ICML | Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. | Danny Halawi, Alexander Wei, Eric Wallace, Tony Tong Wang, Nika Haghtalab, Jacob Steinhardt |
| 2023 | AAAI | Competition, Alignment, and Equilibria in Digital Marketplaces. | Meena Jagadeesan, Michael I. Jordan, Nika Haghtalab |
| 2023 | COLT | Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes. | Pranjal Awasthi, Nika Haghtalab, Eric Zhao |
| 2023 | STOC | Stochastic Minimum Vertex Cover in General Graphs: A 3/2-Approximation. | Mahsa Derakhshan, Naveen Durvasula, Nika Haghtalab |
| 2021 | FOCS | Smoothed Analysis with Adaptive Adversaries. | Nika Haghtalab, Tim Roughgarden, Abhishek Shetty |
| 2021 | ICML | One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning. | Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao |
| 2020 | IJCAI | Maximizing Welfare with Incentive-Aware Evaluation Mechanisms. | Nika Haghtalab, Nicole Immorlica, Brendan Lucier, Jack Z. Wang |
| 2019 | AIES | Algorithmic Greenlining: An Approach to Increase Diversity. | Christian Borgs, Jennifer T. Chayes, Nika Haghtalab, Adam Tauman Kalai, Ellen Vitercik |
| 2019 | AISTATS | Structured Robust Submodular Maximization: Offline and Online Algorithms. | Nima Anari, Nika Haghtalab, Seffi Naor, Sebastian Pokutta, Mohit Singh, Alfredo Torrico |
| 2019 | IJCAI | The Provable Virtue of Laziness in Motion Planning. | Nika Haghtalab, Simon Mackenzie, Ariel D. Procaccia, Oren Salzman, Siddhartha S. Srinivasa |
| 2019 | SAGT | Computing Stackelberg Equilibria of Large General-Sum Games. | Avrim Blum, Nika Haghtalab, MohammadTaghi Hajiaghayi, Saeed Seddighin |
| 2018 | AAAI | Algorithms for Generalized Topic Modeling. | Avrim Blum, Nika Haghtalab |
| 2018 | AAAI | Weighted Voting Via No-Regret Learning. | Nika Haghtalab, Ritesh Noothigattu, Ariel D. Procaccia |
| 2017 | COLT | Efficient PAC Learning from the Crowd. | Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour |
| 2017 | FOCS | Oracle-Efficient Online Learning and Auction Design. | Miroslav Dudk, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan |
| 2017 | SODA | Opting Into Optimal Matchings. | Avrim Blum, Ioannis Caragiannis, Nika Haghtalab, Ariel D. Procaccia, Eviatar B. Procaccia, Rohit Vaish |
| 2016 | COLT | Learning and 1-bit Compressed Sensing under Asymmetric Noise. | Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Hongyang Zhang |
| 2016 | ICALP | k-Center Clustering Under Perturbation Resilience. | Maria-Florina Balcan, Nika Haghtalab, Colin White |
| 2016 | IJCAI | Three Strategies to Success: Learning Adversary Models in Security Games. | Nika Haghtalab, Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Ariel D. Procaccia, Milind Tambe |
| 2015 | COLT | Efficient Learning of Linear Separators under Bounded Noise. | Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner |
| 2015 | ICDM | Monitoring Stealthy Diffusion. | Nika Haghtalab, Aron Laszka, Ariel D. Procaccia, Yevgeniy Vorobeychik, Xenofon D. Koutsoukos |
| 2014 | AAAI | Lazy Defenders Are Almost Optimal against Diligent Attackers. | Avrim Blum, Nika Haghtalab, Ariel D. Procaccia |
| 2014 | ICML | Clustering in the Presence of Background Noise. | Shai Ben-David, Nika Haghtalab |