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Learning Theory

Learning theory

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Showing 351–400 of 852 papers

TitleStatusHype
On establishing learning separations between classical and quantum machine learning with classical data—0
DeepHider: A Covert NLP Watermarking Framework Based on Multi-task Learning—0
Proof-of-Learning is Currently More Broken Than You ThinkCode0
What can we Learn by Predicting Accuracy?—0
V-Coder: Adaptive AutoEncoder for Semantic Disclosure in Knowledge Graphs—0
Masked Spatial-Spectral Autoencoders Are Excellent Hyperspectral Defenders—0
Modeling Non-Cooperative Dialogue: Theoretical and Empirical InsightsCode0
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting—0
Binary Iterative Hard Thresholding Converges with Optimal Number of Measurements for 1-Bit Compressed Sensing—0
q-Learning in Continuous Time—0
Multimodal large language models for inclusive collaboration learning tasks—0
Understanding Benign Overfitting in Gradient-Based Meta Learning—0
Gray Learning from Non-IID Data with Out-of-distribution SamplesCode0
Adversarial Robustness is at Odds with Lazy Training—0
Theory of Machine Learning with Limited Data—0
Scientific Inference With Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena—0
Adaptive Frequency Band Selection for Accurate and Fast Positioning utilizing SOPs—0
Learning in Observable POMDPs, without Computationally Intractable Oracles—0
Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization—0
Straggler-Resilient Personalized Federated LearningCode0
Uncertainty Estimation in Machine Learning—0
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rulesCode0
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior—0
An Analytic Framework for Robust Training of Artificial Neural NetworksCode0
Learning ReLU networks to high uniform accuracy is intractableCode0
Learning Distributions by Generative Adversarial Networks: Approximation and Generalization—0
Why does Throwing Away Data Improve Worst-Group Error?—0
Survey on Fair Reinforcement Learning: Theory and Practice—0
A Note on the Chernoff Bound for Random Variables in the Unit Interval—0
Detailed Balanced Chemical Reaction Networks as Generalized Boltzmann Machines—0
Universal CachingCode0
Investigating Generalization by Controlling Normalized MarginCode0
Intrinsic Gradient Compression for Scalable and Efficient Federated Learning—0
Adaptive hybrid activation function for deep neural networksCode0
Learning Theory of Mind via Dynamic Traits Attribution—0
Learning from many trajectories—0
Tight Bounds on the Hardness of Learning Simple Nonparametric Mixtures—0
Knowledge Distillation: Bad Models Can Be Good Role Models—0
Learning Losses for Strategic Classification—0
Generalization bounds for learning under graph-dependence: A survey—0
Learning from Label Proportions with Instance-wise ConsistencyCode0
Learning curves for the multi-class teacher-student perceptronCode0
Optimal Rejection Function Meets Character Recognition Tasks—0
Approximability and Generalisation—0
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms—0
A Characterization of Multiclass Learnability—0
Towards a unified view of unsupervised non-local methods for image denoising: the NL-Ridge approachCode0
Contrasting random and learned features in deep Bayesian linear regression—0
Generalized Label Shift Correction via Minimum Uncertainty Principle: Theory and Algorithm—0
Towards Unsupervised Domain Adaptation via Domain-Transformer—0
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