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Learning Theory

Learning theory

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Showing 351–400 of 852 papers

TitleStatusHype
Convergence Rates for Learning Linear Operators from Noisy Data—0
A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees—0
Improving Generalization of Sequence Encoder-Decoder Networks for Inverse Imaging of Cardiac Transmembrane Potential—0
Improving Noise Robustness through Abstractions and its Impact on Machine Learning—0
Incomplete Multi-view Multi-label Classification via a Dual-level Contrastive Learning Framework—0
Inductive supervised quantum learning—0
Inference in Sparse Graphs with Pairwise Measurements and Side Information—0
Inferring Ingrained Remote Information in AC Power Flows Using Neuromorphic Modality Regime—0
Exponential Hardness of Reinforcement Learning with Linear Function Approximation—0
Credal Learning Theory—0
Information Science Principles of Machine Learning: A Causal Chain Meta-Framework Based on Formalized Information Mapping—0
Information-Theoretic Analysis of Minimax Excess Risk—0
Information-theoretic generalization bounds for learning from quantum data—0
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization—0
Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise—0
Integrated analysis of the urban water-electricity demand nexus in the Midwestern United States—0
Interplay between depth of neural networks and locality of target functions—0
Analyzing Data Selection Techniques with Tools from the Theory of Information Losses—0
Interpreting Deep Learning: The Machine Learning Rorschach Test?—0
Intrinisic Gradient Compression for Federated Learning—0
Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles—0
Intrinsic Gradient Compression for Scalable and Efficient Federated Learning—0
Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation—0
Data Selection for ERMs—0
Beyond the Low-Degree Algorithm: Mixtures of Subcubes and Their Applications—0
Is Algorithmic Stability Testable? A Unified Framework under Computational Constraints—0
Exploiting Heterogeneity in Operational Neural Networks by Synaptic Plasticity—0
Is Transductive Learning Equivalent to PAC Learning?—0
Just Mix Once: Worst-group Generalization by Group Interpolation—0
Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes—0
Kernel Methods for Linear Discrete-Time Equations—0
On the Existence of Simpler Machine Learning Models—0
Knowledge Distillation: Bad Models Can Be Good Role Models—0
Knowledge Graph Embedding: A Probabilistic Perspective and Generalization Bounds—0
Labeled sample compression schemes for complexes of oriented matroids—0
Large Language Models at Work in China's Labor Market—0
DeepHider: A Covert NLP Watermarking Framework Based on Multi-task Learning—0
Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels -- Attacks and Defenses—0
Transductive Learning Is Compact—0
Deep Learning and Continuous Representations for Natural Language Processing—0
Explaining generalization in deep learning: progress and fundamental limits—0
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers—0
Deep learning generalizes because the parameter-function map is biased towards simple functions—0
A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution—0
Learning-Based Compressive MRI—0
Beyond Statistical Similarity: Rethinking Metrics for Deep Generative Models in Engineering Design—0
Deep Learning Optimization Theory - Trajectory Analysis of Gradient Descent—0
Learning circuits with few negations—0
A Survey on Optimal Transport for Machine Learning: Theory and Applications—0
An induction proof of the backpropagation algorithm in matrix notation—0
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