Bo Dai

DF$^2$: Distribution-Free Decision-Focused Learning UAI 2025 EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing ICLR 2025 Efficient Duple Perturbation Robustness in Low-rank MDPs L4DC 2025 Efficient Online Reinforcement Learning for Diffusion Policy ICML 2025 Faster WIND: Accelerating Iterative Best-of-N Distillation for LLM Alignment AISTATS 2025 Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games ICML 2025 Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models ICLR 2025 Primal-Dual Spectral Representation for Off-policy Evaluation AISTATS 2025 Scalable spectral representations for multiagent reinforcement learning in network MDPs AISTATS 2025 Spectral Representation for Causal Estimation with Hidden Confounders AISTATS 2025 Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF ICLR 2025 BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models ICML 2024 Diffusion Spectral Representation for Reinforcement Learning NeurIPS 2024 HYDRA: Model Factorization Framework for Black-Box LLM Personalization NeurIPS 2024 Probabilistic Adaptation of Black-Box Text-to-Video Models ICLR 2024 Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning ICML 2024 Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates NeurIPS 2024 Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation ICML 2024 UQE: A Query Engine for Unstructured Databases NeurIPS 2024 AdaPlanner: Adaptive Planning from Feedback with Language Models NeurIPS 2023 Any-scale Balanced Samplers for Discrete Space ICLR 2023 Discrete Langevin Samplers via Wasserstein Gradient Flow AISTATS 2023 Energy-based Predictive Representations for Partially Observed Reinforcement Learning UAI 2023 Latent Variable Representation for Reinforcement Learning ICLR 2023 Learning Universal Policies via Text-Guided Video Generation NeurIPS 2023 Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023 On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval EMNLP 2023 Ordering-based Conditions for Global Convergence of Policy Gradient Methods NeurIPS 2023 Score-based Continuous-time Discrete Diffusion Models ICLR 2023 Spectral Decomposition Representation for Reinforcement Learning ICLR 2023 Stochastic Gradient Succeeds for Bandits ICML 2023 A free lunch from the noise: Provable and practical exploration for representation learning UAI 2022 Making Linear MDPs Practical via Contrastive Representation Learning ICML 2022 Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization ICML 2022 Model Selection in Batch Policy Optimization ICML 2022 Neural Stochastic Dual Dynamic Programming ICLR 2022 Offline Policy Selection under Uncertainty AISTATS 2022 On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games NeurIPS 2022 Oracle Inequalities for Model Selection in Offline Reinforcement Learning NeurIPS 2022 SMARTAVE: Structured Multimodal Transformer for Product Attribute Value Extraction EMNLP 2022 The Curse of Passive Data Collection in Batch Reinforcement Learning AISTATS 2022 The Role of Baselines in Policy Gradient Optimization NeurIPS 2022 Understanding and Leveraging Overparameterization in Recursive Value Estimation ICLR 2022 Combiner: Full Attention Transformer with Sparse Computation Cost NeurIPS 2021 LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs ICML 2021 Learning to Defend by Learning to Attack AISTATS 2021 Leveraging Non-uniformity in First-order Non-convex Optimization ICML 2021 Nearly Horizon-Free Offline Reinforcement Learning NeurIPS 2021 On the Optimality of Batch Policy Optimization Algorithms ICML 2021 Overcoming Catastrophic Forgetting by Bayesian Generative Regularization ICML 2021 Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach EMNLP 2021 Towards understanding retrosynthesis by energy-based models NeurIPS 2021 Understanding the Effect of Stochasticity in Policy Optimization NeurIPS 2021 Batch Stationary Distribution Estimation ICML 2020 CoinDICE: Off-Policy Confidence Interval Estimation NeurIPS 2020 Differentiable Top-k with Optimal Transport NeurIPS 2020 Energy-Based Processes for Exchangeable Data ICML 2020 Escaping the Gravitational Pull of Softmax NeurIPS 2020 Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration NeurIPS 2020 Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees ICLR 2020 Off-Policy Evaluation via the Regularized Lagrangian NeurIPS 2020 Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach NeurIPS 2020 Scalable Deep Generative Modeling for Sparse Graphs ICML 2020 DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections NeurIPS 2019 Energy-Inspired Models: Learning with Sampler-Induced Distributions NeurIPS 2019 Exponential Family Estimation via Adversarial Dynamics Embedding NeurIPS 2019 Kernel Exponential Family Estimation via Doubly Dual Embedding AISTATS 2019 Meta Architecture Search NeurIPS 2019 Retrosynthesis Prediction with Conditional Graph Logic Network NeurIPS 2019 Boosting the Actor with Dual Critic ICLR 2018 Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification NeurIPS 2018 Coupled Variational Bayes via Optimization Embedding NeurIPS 2018 Decoupled Networks CVPR 2018 Learning Steady-States of Iterative Algorithms over Graphs ICML 2018 Learning towards Minimum Hyperspherical Energy NeurIPS 2018 Multi-scale Nystrom Method AISTATS 2018 Predictive Approximate Bayesian Computation via Saddle Points NeurIPS 2018 SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation ICML 2018 Structured Inference for Recurrent Hidden Semi-markov Model IJCAI 2018 Syntax-Directed Variational Autoencoder for Structured Data ICLR 2018 Towards Black-box Iterative Machine Teaching ICML 2018 Deep Hyperspherical Learning NeurIPS 2017 Iterative Machine Teaching ICML 2017 Learning from Conditional Distributions via Dual Embeddings AISTATS 2017 Stochastic Generative Hashing ICML 2017 Discriminative Embeddings of Latent Variable Models for Structured Data ICML 2016 Provable Bayesian Inference via Particle Mirror Descent AISTATS 2016 Nonparametric Estimation of Multi-View Latent Variable Models ICML 2014 Scalable Kernel Methods via Doubly Stochastic Gradients NeurIPS 2014 Robust Low Rank Kernel Embeddings of Multivariate Distributions NeurIPS 2013