#Machine Learning Theory
Latest news articles tagged with "Machine Learning Theory". Follow the timeline of events, related topics, and entities.
Articles (5)
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🇺🇸 A Model-Free Universal AI
[USA]
arXiv:2602.23242v1 Announce Type: new Abstract: In general reinforcement learning, all established optimal agents, including AIXI, are model-based, explicitly maintaining and using environment models...
Related: #Artificial Intelligence, #Reinforcement Learning -
🇺🇸 From Shallow Bayesian Neural Networks to Gaussian Processes: General Convergence, Identifiability and Scalable Inference
[USA]
arXiv:2602.22492v1 Announce Type: cross Abstract: In this work, we study scaling limits of shallow Bayesian neural networks (BNNs) via their connection to Gaussian processes (GPs), with an emphasis o...
Related: #Statistical Modeling, #Computational Efficiency, #Neural Networks -
🇺🇸 Does Order Matter : Connecting The Law of Robustness to Robust Generalization
[USA]
arXiv:2602.20971v1 Announce Type: cross Abstract: Bubeck and Sellke (2021) pose as an open problem the connection between the law of robustness and robust generalization. The law of robustness states...
Related: #Robust AI, #Mathematical Foundations -
🇺🇸 DiffusionBlocks: Block-wise Neural Network Training via Diffusion Interpretation
[USA]
arXiv:2506.14202v3 Announce Type: replace-cross Abstract: End-to-end backpropagation requires storing activations throughout all layers, creating memory bottlenecks that limit model scalability. Exis...
Related: #Neural Network Training, #Transformer Scalability, #Memory Optimization, #Backpropagation -
🇺🇸 The Median is Easier than it Looks: Approximation with a Constant-Depth, Linear-Width ReLU Network
[USA]
arXiv:2602.07219v1 Announce Type: cross Abstract: We study the approximation of the median of $d$ inputs using ReLU neural networks. We present depth-width tradeoffs under several settings, culminati...
Related: #Neural Networks, #Computational Complexity