Cyrus Cousins - RankMe

49 papers A* 9A 7B 2Journal 23Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Moral Change or Noise? On Problems of Aligning AI with Temporally Unstable Human Feedback. AAAI Vijay Keswani, Cyrus Cousins, Breanna K. Nguyen, Vincent Conitzer, Hoda Heidari, Jana Schaich Borg, Walter Sinnott-Armstrong
2025	J	`jnl`	Deploying Fair and Efficient Course Allocation Mechanisms. CoRR George Bissias, Cyrus Cousins, Paula Navarrete Diaz, Yair Zick
2025	—	`conf`	Discrimination Induced by Algorithmic Recourse Objectives. FAccT Nicholas Perello, Cyrus Cousins, Yair Zick, Przemyslaw A. Grabowicz
2025	J	`jnl`	Moral Change or Noise? On Problems of Aligning AI With Temporally Unstable Human Feedback. CoRR Vijay Keswani, Cyrus Cousins, Breanna K. Nguyen, Vincent Conitzer, Hoda Heidari, Jana Schaich Borg, Walter Sinnott-Armstrong
2025	J	`jnl`	Towards Cognitively-Faithful Decision-Making Models to Improve AI Alignment. CoRR Cyrus Cousins, Vijay Keswani, Vincent Conitzer, Hoda Heidari, Jana Schaich Borg, Walter Sinnott-Armstrong
2024	J	`jnl`	Algorithms and Analysis for Optimizing Robust Objectives in Fair Machine Learning. CoRR Cyrus Cousins
2024	A*	`conf`	Fair and Welfare-Efficient Constrained Multi-Matchings under Uncertainty. NeurIPS Elita A. Lobo, Justin Payan, Cyrus Cousins, Yair Zick
2024	J	`jnl`	Fair and Welfare-Efficient Constrained Multi-matchings under Uncertainty. CoRR Elita A. Lobo, Justin Payan, Cyrus Cousins, Yair Zick
2024	J	`jnl`	On Welfare-Centric Fair Reinforcement Learning. RLJ Cyrus Cousins, Kavosh Asadi, Elita A. Lobo, Michael Littman
2024	J	`jnl`	Percentile Criterion Optimization in Offline Reinforcement Learning. CoRR Elita A. Lobo, Cyrus Cousins, Yair Zick, Marek Petrik
2024	A	`conf`	To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models. AISTATS Cyrus Cousins, I. Elizabeth Kumar, Suresh Venkatasubramanian
2024	J	`jnl`	To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models. CoRR Cyrus Cousins, I. Elizabeth Kumar, Suresh Venkatasubramanian
2023	J	`jnl`	Bavarian: Betweenness Centrality Approximation with Variance-aware Rademacher Averages. ACM Trans. Knowl. Discov. Data Cyrus Cousins, Chloe Wohlgemuth, Matteo Riondato
2023	J	`jnl`	Dividing Good and Better Items Among Agents with Submodular Valuations. CoRR Cyrus Cousins, Vignesh Viswanathan, Yair Zick
2023	—	`conf`	Dividing Good and Great Items Among Agents with Bivalued Submodular Valuations. WINE Cyrus Cousins, Vignesh Viswanathan, Yair Zick
2023	B	`conf`	Into the Unknown: Assigning Reviewers to Papers with Uncertain Affinities. SAGT Cyrus Cousins, Justin Payan, Yair Zick
2023	J	`jnl`	Into the Unknown: Assigning Reviewers to Papers with Uncertain Affinities. CoRR Cyrus Cousins, Justin Payan, Yair Zick
2023	A	`conf`	Learning Properties in Simulation-Based Games. AAMAS Cyrus Cousins, Bhaskar Mishra, Enrique Areyan Viqueira, Amy Greenwald
2023	A*	`conf`	Percentile Criterion Optimization in Offline Reinforcement Learning. NeurIPS Cyrus Cousins, Elita A. Lobo, Marek Petrik, Yair Zick
2023	A	`conf`	Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare. AISTATS Cyrus Cousins
2023	—	`conf`	The Good, the Bad and the Submodular: Fairly Allocating Mixed Manna Under Order-Neutral Submodular Preferences. WINE Cyrus Cousins, Vignesh Viswanathan, Yair Zick
2023	J	`jnl`	The Good, the Bad and the Submodular: Fairly Allocating Mixed Manna Under Order-Neutral Submodular Preferences. CoRR Cyrus Cousins, Vignesh Viswanathan, Yair Zick
2022	J	`jnl`	Computational and Data Requirements for Learning Generic Properties of Simulation-Based Games. CoRR Cyrus Cousins, Bhaskar Mishra, Enrique Areyan Viqueira, Amy Greenwald
2022	J	`jnl`	MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. ACM Trans. Knowl. Discov. Data Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
2022	J	`jnl`	Regret Pruning for Learning Equilibria in Simulation-Based Games. CoRR Bhaskar Mishra, Cyrus Cousins, Amy Greenwald
2022	—	`conf`	Uncertainty and the Social Planner's Problem: Why Sample Complexity Matters. FAccT Cyrus Cousins
2021	A*	`conf`	Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees. ICML Alessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen H. Bach, Eli Upfal
2021	A*	`conf`	An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning. NeurIPS Cyrus Cousins
2021	J	`jnl`	An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning. CoRR Cyrus Cousins
2021	A*	`conf`	Bavarian: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages. KDD Cyrus Cousins, Chloe Wohlgemuth, Matteo Riondato
2021	—	`—`	Bounds and Applications of Concentration of Measure in Fair Machine Learning and Data Science. Cyrus Cousins
2021	A*	`conf`	Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds. NeurIPS Shahrzad Haddadan, Yue Zhuang, Cyrus Cousins, Eli Upfal
2021	J	`jnl`	Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds. CoRR Shahrzad Haddadan, Yue Zhuang, Cyrus Cousins, Eli Upfal
2021	A	`conf`	Learning Competitive Equilibria in Noisy Combinatorial Markets. AAMAS Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald
2021	J	`jnl`	Learning Competitive Equilibria in Noisy Combinatorial Markets. CoRR Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald
2020	A	`conf`	Improved Algorithms for Learning Equilibria in Simulation-Based Games. AAMAS Enrique Areyan Viqueira, Cyrus Cousins, Amy Greenwald
2020	A*	`conf`	MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. KDD Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
2020	J	`jnl`	MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. CoRR Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato
2020	J	`jnl`	Making mean-estimation more efficient using an MCMC trace variance approach: DynaMITE. CoRR Cyrus Cousins, Shahrzad Haddadan, Eli Upfal
2020	A*	`conf`	Sharp uniform convergence bounds through empirical centralization. NeurIPS Cyrus Cousins, Matteo Riondato
2019	J	`jnl`	CaDET: interpretable parametric conditional density estimation with decision trees and forests. Mach. Learn. Cyrus Cousins, Matteo Riondato
2019	A	`conf`	Empirical Mechanism Design: Designing Mechanisms from Data. UAI Enrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, Amy Greenwald
2019	J	`jnl`	Learning Equilibria of Simulation-Based Games. CoRR Enrique Areyan Viqueira, Cyrus Cousins, Eli Upfal, Amy Greenwald
2019	A	`conf`	Learning Simulation-Based Games from Data. AAMAS Enrique Areyan Viqueira, Amy Greenwald, Cyrus Cousins, Eli Upfal
2018	—	`conf`	Towards Interactive Curation & Automatic Tuning of ML Pipelines. DEEM@SIGMOD Carsten Binnig, Benedetto Buratti, Yeounoh Chung, Cyrus Cousins, Tim Kraska, Zeyuan Shang, Eli Upfal, Robert C. Zeleznik, Emanuel Zgraggen
2018	J	`jnl`	Uniform Convergence Bounds for Codec Selection. CoRR Clayton Sanford, Cyrus Cousins, Eli Upfal
2017	—	`conf`	Scalable FRaC Variants: Anomaly Detection for Precision Medicine. IPDPS Workshops Cyrus Cousins, Christopher M. Pietras, Donna K. Slonim
2017	B	`conf`	The k-Nearest Representatives Classifier: A Distance-Based Classifier with Strong Generalization Bounds. DSAA Cyrus Cousins, Eli Upfal
2017	—	`conf`	Towards Interactive Data Exploration. BIRTE (Revised Selected Papers) Carsten Binnig, Fuat Basik, Benedetto Buratti, Ugur Çetintemel, Yeounoh Chung, Andrew Crotty, Cyrus Cousins, Dylan Ebert, Philipp Eichmann, Alex Galakatos, Benjamin Hättasch, Amir Ilkhechi, Tim Kraska, Zeyuan Shang, Isabella Tromba, Arif Usta, Prasetya Ajie Utama, Eli Upfal, Linnan Wang, Nathaniel Weir, Robert C. Zeleznik, Emanuel Zgraggen