Stochastic Processes

Keep-Alive Caching for the Hawkes process UAI 2023 Knowledge Graph Embeddings using Neural Ito Process: From Multiple Walks to Stochastic Trajectories ACL 2023 Label Propagation with Weak Supervision ICLR 2023 Langevin Diffusion Variational Inference AISTATS 2023 Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning ICML 2023 Large deviations rates for stochastic gradient descent with strongly convex functions AISTATS 2023 Last Switch Dependent Bandits with Monotone Payoff Functions ICML 2023 Latent Positional Information is in the Self-Attention Variance of Transformer Language Models Without Positional Embeddings ACL 2023 LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection (Student Abstract) AAAI 2023 Learning-augmented private algorithms for multiple quantile release ICML 2023 Learning Energy-Based Prior Model with Diffusion-Amortized MCMC NeurIPS 2023 Learning Globally Smooth Functions on Manifolds ICML 2023 Learning Hidden Markov Models When the Locations of Missing Observations are Unknown ICML 2023 Learning Markov Random Fields for Combinatorial Structures via Sampling through Lovász Local Lemma AAAI 2023 Learning Mean-Field Games with Discounted and Average Costs JMLR 2023 Learning Physical Models that Can Respect Conservation Laws ICML 2023 Learning Rate Schedules in the Presence of Distribution Shift ICML 2023 Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling ICML 2023 Linear Stochastic Bandits over a Bit-Constrained Channel L4DC 2023 Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains ICML 2023 Local Dependence Graphs for Discrete Time Processes CLeaR 2023 Local Message Passing on Frustrated Systems UAI 2023 Logarithmic regret in communicating MDPs: Leveraging known dynamics with bandits ACML 2023 Loosely consistent emphatic temporal-difference learning UAI 2023 Loss Dynamics of Temporal Difference Reinforcement Learning NeurIPS 2023