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← Optimization & Theory
Machine Learning
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Optimization & Theory
›
Learning Theory
5,312 papers
Papers per year
2001: 1
2002: 16
2003: 16
2004: 15
2005: 17
2006: 30
2007: 32
2008: 32
2009: 34
2010: 66
2011: 76
2012: 74
2013: 94
2014: 115
2015: 123
2016: 128
2017: 185
2018: 219
2019: 390
2020: 466
2021: 640
2022: 664
2023: 799
2024: 688
2025: 307
2026: 85
Papers
Iterative Classroom Teaching
AAAI 2019
Learning Set Functions with Limited Complementarity
AAAI 2019
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications
AAAI 2019
Capacity Control of ReLU Neural Networks by Basis-Path Norm
AAAI 2019
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models
AAAI 2019
Performance Guarantees for Homomorphisms beyond Markov Decision Processes
AAAI 2019
Finding All Bayesian Network Structures within a Factor of Optimal
AAAI 2019
Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications
AAAI 2019
Efficient Solving of Birds of a Feather Puzzles
AAAI 2019
Learning and the Unknown: Surveying Steps toward Open World Recognition
AAAI 2019
A Theory of State Abstraction for Reinforcement Learning
AAAI 2019
Comparing Sample-Wise Learnability across Deep Neural Network Models
AAAI 2019
Relating RNN Layers with the Spectral WFA Ranks in Sequence Modelling
ACL 2019
Multi-Element Long Distance Dependencies: Using SPk Languages to Explore the Characteristics of Long-Distance Dependencies
ACL 2019
Semantic Expressive Capacity with Bounded Memory
ACL 2019
Correlating Neural and Symbolic Representations of Language
ACL 2019
CNNs found to jump around more skillfully than RNNs: Compositional Generalization in Seq2seq Convolutional Networks
ACL 2019
Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings
ACL 2019
Simultaneous Translation with Flexible Policy via Restricted Imitation Learning
ACL 2019
Latent Structure Models for Natural Language Processing
ACL 2019
ResNet and Batch-normalization Improve Data Separability
ACML 2019
Minimax Online Prediction of Varying Bernoulli Process under Variational Approximation
ACML 2019
Learning to Sample Hard Instances for Graph Algorithms
ACML 2019
A Generalization Bound for Online Variational Inference
ACML 2019
Error bounds for sparse classifiers in high-dimensions
AISTATS 2019
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