Lillian Ratliff
Associate Professor; Afroze and Sherali Dhanani Endowed Faculty Fellow
Studies learning in games, combining game theory, machine learning and optimization.
Lillian Ratliff's lab at UW works on learning theory & optimization and reasoning & neuro-symbolic AI. 37 papers since 2023. 6 PhD students. 12 alumni. Applications close .
At a glance
- papers, 2023–2026
- 10/ year
- at T1 venues
- 0%
- PhD students
- 6
- MS students
- 0
- alumni listed
- 12
Papers by yearfrom the lab homepage, 2023–2026
- 9 papers2026 · T1 0 · collecting
- 13 papers2025 · T1 0
- 9 papers2024 · T1 0
- 6 papers2023 · T1 0
T1 venuesOther
Research focuspaper titles that use each topic's words
- Learning theory & optimization12 papers
- games12 papers
- Reasoning & neuro-symbolic AI1 paper
- studies learning0 papers
- game theory0 papers
Paper list
From the lab homepage.
20269 papers
- NeurIPS · ·ABC-Align: Prediction-Powered Alignment with Adaptive Bias Control (opens in a new tab)
- UAI · ·Achieving Alignment Through Adaptive Play: Helping Optimize Objectives Without Observing Them (opens in a new tab)
- NeurIPS · ·Adaptive Calibration in Non-Stationary Environments (opens in a new tab)
- UAI · ·Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing (opens in a new tab)
- AISTATS · ·Efficient Uncoupled Learning Dynamics with $O(T^-1/4)$ Last-Iterate Convergence in Bilinear Saddle-Point Problems over Convex Sets under Bandit Feedback (opens in a new tab)
- Conference on Learning Theory · ·Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation (opens in a new tab)
- Proceedings of the International Conference on Machine Learning · ·Revisiting the Bertrand Paradox via Equilibrium Analysis of No-regret Learners (opens in a new tab)
- Reinforcement Learning Conference · ·Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation (opens in a new tab)
- Conference on Robot Learning · ·Topreward: Token probabilities as hidden zero-shot rewards for robotics (opens in a new tab)
202513 papers
- Proceedings of International Conference on Space Operations · ·A Transformer-Based Deep Learning Approach to Anomaly Detection of High-Bandwidth Multivariate Time-Series Satellite Communications (opens in a new tab)
- ICML · ·Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic Agents. (opens in a new tab)
- INFORMS Journal on Optimization · ·Function Design for Improved Competitive Ratio in Online Resource Allocation with Procurement Costs (opens in a new tab)
- Scientific reports · ·Human adaptation to adaptive machines converges to game-theoretic equilibria (opens in a new tab)
- NeurIPS · ·Improved Regret and Contextual Linear Extension for Pandora\textquotesingle s Box and Prophet Inequality (opens in a new tab)
- NeurIPS WorkshopLatent Nonlinear Wave Dynamics in Image Datasets and Autoencoder Reconstructions (opens in a new tab)
- ICML · ·Learning to incentivize in repeated principal-agent problems with adversarial agent arrivals (opens in a new tab)
- International Symposium on Algorithmic Game Theory · ·On the limitations and possibilities of Nash regret minimization in zero-sum matrix games under noisy feedback (opens in a new tab)
- NeurIPS · ·On the Universal Near Optimality of Hedge in Combinatorial Settings (opens in a new tab)
- ICML · ·Principal-agent bandit games with self-interested and exploratory learning agents (opens in a new tab)
- ACM Transactions on Economics and Computation · ·Query-efficient algorithm to find all nash equilibria in a two-player zero-sum matrix game (opens in a new tab)
- ICML · ·S4S: Solving for a Fast Diffusion Model Solver (opens in a new tab)
20249 papers
- NeurIPS WorkshopConformal Reasoning: Uncertainty Estimation in Interactive Environments (opens in a new tab)
- NeurIPS · ·Coupled Wasserstein gradient flows for min-max and cooperative games (opens in a new tab)
- UAI · ·Efficient Interactive Maximization of BP and Weakly Submodular Objectives. (opens in a new tab)
- AISTATS · ·Emergent specialization from participation dynamics and multi-learner retraining (opens in a new tab)
- CDC · ·Follower agnostic learning in stackelberg games (opens in a new tab)
- NeurIPS · ·Initializing Services in Interactive ML Systems for Diverse Users (opens in a new tab)
- ACC · ·Learning in stochastic stackelberg games (opens in a new tab)
- AISTATS · ·Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits (opens in a new tab)
- NeurIPS · ·Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning (opens in a new tab)
20236 papers
- Automatica · ·Adaptive constraint satisfaction for markov decision process congestion games: Application to transportation networks (opens in a new tab)
- AISTATS · ·Approximate Regions of Attraction in Learning with Decision-Dependent Distributions (opens in a new tab)
- IEEE Control Systems Letters · ·Consistent conjectural variations equilibria: Characterization and stability for a class of continuous games (opens in a new tab)
- AISTATS · ·Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games (opens in a new tab)
- JMLR · ·Multiplayer Performative Prediction: Learning in Decision-Dependent Games (opens in a new tab)
- NeurIPS · ·Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows (opens in a new tab)
Where alumni went12 listed
Apply to UWFall 2027
UW Allen School Computer Science PhD
- Round
- Single round
- Opens
- GRE
- not required
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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