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Showing 501–550 of 852 papers

TitleStatusHype
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal InferenceCode0
Learning Description Logic Ontologies. Five Approaches. Where Do They Stand?—0
Why is AI hard and Physics simple?—0
Understanding the role of importance weighting for deep learning—0
Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels -- Attacks and Defenses—0
Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning—0
On the Complexity of Learning Description Logic Ontologies—0
On the Impact of Applying Machine Learning in the Decision-Making of Self-Adaptive Systems—0
A deep learning theory for neural networks grounded in physics—0
Constrained Learning with Non-Convex Losses—0
Learning Prediction Intervals for Regression: Generalization and Calibration—0
Consistent Sparse Deep Learning: Theory and ComputationCode0
Theoretical Understandings of Product Embedding for E-commerce Machine Learning—0
Two Sides of Meta-Learning Evaluation: In vs. Out of DistributionCode0
Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension—0
KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-Zero Training Loss—0
On the robustness of randomized classifiers to adversarial examples—0
Geostatistical Learning: Challenges and OpportunitiesCode0
Double-descent curves in neural networks: a new perspective using Gaussian processes—0
Distribution Free Uncertainty for the Minimum Norm Solution of Over-parameterized Linear Regression—0
Private learning implies quantum stability—0
Local and Global Uniform Convexity Conditions—0
On the Hardness of PAC-learning Stabilizer States with Noise—0
Effects of quantum resources on the statistical complexity of quantum circuits—0
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels—0
Query Complexity of Least Absolute Deviation Regression via Robust Uniform Convergence—0
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation—0
f-Domain-Adversarial Learning: Theory and Algorithms for Unsupervised Domain Adaptation with Neural Networks—0
Mirror Sample Based Distribution Alignment for Unsupervised Domain Adaption—0
Illuminating Dark Knowledge via Random Matrix Ensembles—0
Maximum-Likelihood Quantum State Tomography by Soft-Bayes—0
Continuity of Generalized Entropy and Statistical Learning—0
Risk Guarantees for End-to-End Prediction and Optimization Processes—0
The VIP Gallery for Video Processing Education—0
Blackwell Online Learning for Markov Decision Processes—0
A Tight Lower Bound for Uniformly Stable Algorithms—0
Recent advances in deep learning theory—0
Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise—0
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning—0
Reconstructing decision trees—0
Notes on Deep Learning Theory—0
Quantum learning algorithms imply circuit lower bounds—0
Margin-Based Transfer Bounds for Meta Learning with Deep Feature Embedding—0
On a Chatbot Navigating a User through a Concept-Based Knowledge Model—0
A Convenient Infinite Dimensional Framework for Generative Adversarial Learning—0
A General Framework for Distributed Inference with Uncertain Models—0
Chaos and Complexity from Quantum Neural Network: A study with Diffusion Metric in Machine Learning—0
Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory—0
Deep Active Learning with Augmentation-based Consistency EstimationCode0
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition—0
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