📐 ML Theory - chris1 · Scour

Near-Optimal Decentralized Stochastic Convex Optimization over Networks

🎮Reinforcement Learning Academic

Variational inference-based prior-informed root cause analysis in closed-loop systems

🎮Reinforcement Learning Academic

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Stein’s method, learning and inference -or- how to really monitor convergence and thin chains

🎲Probability Academic

statmodeling.stat.columbia.edu·

Gu Quanquan Exits ByteSeed: Doubao's Paid Model Conceals Hidden Agenda - 36Kr

Noise-Adaptive High-Probability Regret Bounds for Online Convex Optimization

🎮Reinforcement Learning Academic

Large-scale empirical tuning and comparison of default optimizers for variational inference

🎲Probability Academic

An Empirical Study of Data Scale, Model Complexity, and Input Modalities in Visual Generalization

🧠Neural Networks Academic

Disentanglement with Holographic Reduced Representations

🧠Neural Networks Academic

Variational Proximal Policy Optimization

🎮Reinforcement Learning Academic

Backward Coherence and Hidden-State Stability in Recurrent Neural Networks: A Quasi-Reverse-Martingale Theory

🧠Neural Networks Academic

Constrained Weighted Bayesian Bootstrap

🎲Probability Academic

Deep Learning Based Sparse Array Design with Pre-Steering for Adaptive Beamforming

🧠Neural Networks Academic

A Global Convergence Analysis of Consensus ALADIN for Convex Optimization

🎮Reinforcement Learning Academic

Adaptive Learning Rates with Surrogate Probability for Follow-the-Perturbed-Leader

🎮Reinforcement Learning Academic

Semidefinite-programming hierarchies for classically simulable state families

🧮Algorithms Academic

Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference

🎮Reinforcement Learning Academic

Real-Time and Accurate Collision-Free Teleoperation via Differentiable Constraint-Based Trajectory Planning

🎮Reinforcement Learning Academic

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