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Learning Theory

Learning theory

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Showing 201–250 of 852 papers

TitleStatusHype
Impact of Data Augmentation on QCNNs—0
Optimal Sample Complexity of Contrastive Learning—0
When Is Inductive Inference Possible?—0
Applying statistical learning theory to deep learning—0
Stability and L2-penalty in Model Averaging—0
Information-theoretic generalization bounds for learning from quantum data—0
Generative learning for nonlinear dynamics—0
Learning to Augment Distributions for Out-of-Distribution DetectionCode1
Autonomous Learning of Generative Models with Chemical Reaction Network Ensembles—0
Applications of the Theory of Aggregated Markov Processes in Stochastic Learning Theory—0
Lifting the Veil: Unlocking the Power of Depth in Q-learning—0
On kernel-based statistical learning in the mean field limit—0
The Bayesian Stability Zoo—0
Bi-discriminator Domain Adversarial Neural Networks with Class-Level Gradient AlignmentCode0
An Online Learning Theory of Brokerage—0
Dynamical versus Bayesian Phase Transitions in a Toy Model of Superposition—0
Constructive Large Language Models Alignment with Diverse Feedback—0
SPADE: Sparsity-Guided Debugging for Deep Neural NetworksCode0
Why Do We Need Weight Decay in Modern Deep Learning?Code1
Learnable Extended Activation Function (LEAF) for Deep Neural NetworksCode0
On Continuity of Robust and Accurate Classifiers—0
Sharp Generalization of Transductive Learning: A Transductive Local Rademacher Complexity Approach—0
Learning to Abstain From Uninformative Data—0
On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay—0
Statistical Complexity of Quantum Learning—0
Striking a Balance: An Optimal Mechanism Design for Heterogenous Differentially Private Data Acquisition for Logistic Regression—0
Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles—0
Contrastive Learning as Kernel Approximation—0
Towards Low-Barrier Cybersecurity Research and Education for Industrial Control Systems—0
Improved learning theory for kernel distribution regression with two-stage samplingCode0
Sample Complexity of Robust Learning against Evasion Attacks—0
The Local Learning Coefficient: A Singularity-Aware Complexity MeasureCode1
Learning in Cooperative Multiagent Systems Using Cognitive and Machine ModelsCode0
Large Language Models at Work in China's Labor Market—0
Globe230k: A Benchmark Dense-Pixel Annotation Dataset for Global Land Cover Mapping—0
A deep deformable residual learning network for SAR images segmentation—0
When Deep Learning Meets Multi-Task Learning in SAR ATR: Simultaneous Target Recognition and Segmentation—0
A Strategic Framework for Optimal Decisions in Football 1-vs-1 Shot-Taking Situations: An Integrated Approach of Machine Learning, Theory-Based Modeling, and Game TheoryCode0
Learning invariant representations of time-homogeneous stochastic dynamical systemsCode0
Enhancing Pattern Classification in Support Vector Machines through Matrix Formulation—0
Generalization within in silico screening—0
Credit Assignment: Challenges and Opportunities in Developing Human-like AI Agents—0
Properly Learning Decision Trees with Queries Is NP-Hard—0
A Combinatorial Characterization of Supervised Online Learnability—0
Learning Theory of Distribution Regression with Neural Networks—0
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms—0
Transgressing the boundaries: towards a rigorous understanding of deep learning and its (non-)robustness—0
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space—0
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit—0
Exponential separations between classical and quantum learners—0
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