Learning Theory

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Most implemented papers archive 2025-07-28

30 shown of 140 papers with code (852 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• A Contextual-Bandit Approach to Personalized News Article Recommendation
  28 Feb 2010 12 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 1 pointer-only (licence)
  In this work, we model personalized recommendation of news articles as a contextual bandit problem, a principled approach in which a learning algorithm sequentially selects articles to serve users based on contextual…
• Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks
  6 Jul 2021 3 repositories listed
  Meta learning has attracted much attention recently in machine learning community.
• Transductive Active Learning: Theory and Applications
  13 Feb 2024 2 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  We study a generalization of classical active learning to real-world settings with concrete prediction targets where sampling is restricted to an accessible region of the domain, while prediction targets may lie outside…
• Stabilizing Sharpness-aware Minimization Through A Simple Renormalization Strategy
  14 Jan 2024 2 repositories listed
  Recently, sharpness-aware minimization (SAM) has attracted much attention because of its surprising effectiveness in improving generalization performance.
• The Local Learning Coefficient: A Singularity-Aware Complexity Measure
  23 Aug 2023 2 repositories listed Syntology ran 7 of 8 samples · 1 unverified · 8 pointer-only (licence)
  The Local Learning Coefficient (LLC) is introduced as a novel complexity measure for deep neural networks (DNNs).
• 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 Theory
  27 Jul 2023 2 repositories listed
  To address this issue, we proposed a novel framework to analyze such scenarios based on game theory, where we estimate the expected payoff with machine learning (ML) models, and additional features for ML models were…
• Don't fear the unlabelled: safe semi-supervised learning via simple debiasing
  14 Mar 2022 2 repositories listed
  Our debiasing approach is straightforward to implement and applicable to most deep SSL methods.
• Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks
  25 Nov 2021 2 repositories listed Syntology ran 4 of 7 samples · 3 unverified
  Disobeying the classical wisdom of statistical learning theory, modern deep neural networks generalize well even though they typically contain millions of parameters.
• On Optimal Interpolation In Linear Regression
  21 Oct 2021 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  We identify a regime where the minimum-norm interpolator provably generalizes arbitrarily worse than the optimal response-linear achievable interpolator that we introduce, and validate with numerical experiments that…
• Reverse Engineering the Neural Tangent Kernel
  6 Jun 2021 2 repositories listed
  The development of methods to guide the design of neural networks is an important open challenge for deep learning theory.
• Model Zoo: A Growing "Brain" That Learns Continually
  6 Jun 2021 2 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  We use statistical learning theory and experimental analysis to show how multiple tasks can interact with each other in a non-trivial fashion when a single model is trained on them.
• Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models
  13 Sep 2020 2 repositories listed
  Computational learning theory states that many classes of boolean formulas are learnable in polynomial time.
• Foreseeing the Benefits of Incidental Supervision
  9 Jun 2020 2 repositories listed
  Real-world applications often require improved models by leveraging a range of cheap incidental supervision signals.
• PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
  31 Dec 2019 2 repositories listed Syntology ran 0 of 11 samples · 11 unverified
  We propose an algorithm combining calibrated prediction and generalization bounds from learning theory to construct confidence sets for deep neural networks with PAC guarantees---i.
• A Brain-inspired Algorithm for Training Highly Sparse Neural Networks
  17 Mar 2019 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Concretely, by exploiting the cosine similarity metric to measure the importance of the connections, our proposed method, Cosine similarity-based and Random Topology Exploration (CTRE), evolves the topology of sparse…
• Robust Learning from Untrusted Sources
  29 Jan 2019 2 repositories listed
  Modern machine learning methods often require more data for training than a single expert can provide.
• Generalization in Machine Learning via Analytical Learning Theory
  21 Feb 2018 2 repositories listed
  This paper introduces a novel measure-theoretic theory for machine learning that does not require statistical assumptions.
• Learning a Variational Network for Reconstruction of Accelerated MRI Data
  3 Apr 2017 2 repositories listed
  Due to its high computational performance, i.
• A Semantic Change Detection Network Based on Boundary Detection and Task Interaction for High-Resolution Remote Sensing Images
  26 May 2025 1 repository listed
  In BT-SCD, the boundary detection (BD) task is introduced to enhance the correlation between the SS task and the CD task in SCD, thereby promoting positive reinforcement between SS and CD tasks.
• Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems
  24 May 2025 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  We introduce an encoder-only approach to learn the evolution operators of large-scale non-linear dynamical systems, such as those describing complex natural phenomena.
• auto-fpt: Automating Free Probability Theory Calculations for Machine Learning Theory
  14 Apr 2025 1 repository listed
  A large part of modern machine learning theory often involves computing the high-dimensional expected trace of a rational expression of large rectangular random matrices.
• Double descent in quantum machine learning
  17 Jan 2025 1 repository listed
  The double descent phenomenon challenges traditional statistical learning theory by revealing scenarios where larger models do not necessarily lead to reduced performance on unseen data.
• Gradient Equilibrium in Online Learning: Theory and Applications
  14 Jan 2025 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  We present a new perspective on online learning that we refer to as gradient equilibrium: a sequence of iterates achieves gradient equilibrium if the average of gradients of losses along the sequence converges to zero.
• DDIM sampling for Generative AIBIM, a faster intelligent structural design framework
  30 Dec 2024 1 repository listed
  While the original DDIM was designed for DDPM and the optimization process of PCDM differs from that of DDPM, this paper designs "DDIM sampling for PCDM," which modifies the original DDIM formulations to adapt to the…
• NLPrompt: Noise-Label Prompt Learning for Vision-Language Models
  2 Dec 2024 1 repository listed Syntology ran 4 of 9 samples · 5 unverified · 9 pointer-only (licence)
  This matrix effectively partitions datasets into clean and noisy subsets, allowing for the application of cross-entropy loss to the clean subset and MAE loss to the noisy subset.
• Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method
  29 Sep 2024 1 repository listed Syntology ran 4 of 10 samples · 6 unverified · 10 pointer-only (licence)
  Integrating pretrained vision-language foundation models like CLIP into federated learning has attracted significant attention for enhancing generalization across diverse tasks.
• End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data
  26 Sep 2024 1 repository listed
  In this paper we propose an end-to-end algorithm for indirect data-driven control for bilinear systems with stability guarantees.
• NGD converges to less degenerate solutions than SGD
  7 Sep 2024 1 repository listed
  The number of free parameters, or dimension, of a model is a straightforward way to measure its complexity: a model with more parameters can encode more information.
• Learning Confidence Bounds for Classification with Imbalanced Data
  16 Jul 2024 1 repository listed
  Class imbalance poses a significant challenge in classification tasks, where traditional approaches often lead to biased models and unreliable predictions.
• On the Limitations of Fractal Dimension as a Measure of Generalization
  4 Jun 2024 1 repository listed
  Our work forms a basis for a deeper investigation of the causal relationships between fractal geometry, topological data analysis, and neural network optimization.

Syntology lines on 12 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.