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← Optimization & Theory
Machine Learning
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Optimization & Theory
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Theory
4,950 papers
Papers per year
2000: 1
2001: 2
2002: 3
2003: 3
2004: 9
2005: 4
2006: 32
2007: 25
2008: 31
2009: 25
2010: 37
2011: 37
2012: 45
2013: 76
2014: 66
2015: 72
2016: 102
2017: 156
2018: 246
2019: 353
2020: 447
2021: 567
2022: 646
2023: 741
2024: 670
2025: 426
2026: 128
Papers
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation
NIPS 2022
White-box Testing of NLP models with Mask Neuron Coverage
NAACL 2022
Most Activation Functions Can Win the Lottery Without Excessive Depth
NIPS 2022
Overparameterization from Computational Constraints
NIPS 2022
Why predicting risk can’t identify ‘risk factors’: empirical assessment of model stability in machine learning across observational health databases
MLHC 2022
On the First-Order Rewritability of Ontology-Mediated Queries in Linear Temporal Logic (Extended Abstract)
IJCAI 2022
Learning with Interactive Models over Decision-Dependent Distributions
ACML 2022
The Sample Complexity of One-Hidden-Layer Neural Networks
NIPS 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
NIPS 2022
How Universal is Metonymy? Results from a Large-Scale Multilingual Analysis
NAACL 2022
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity
NIPS 2022
Learning with convolution and pooling operations in kernel methods
NIPS 2022
The Hessian Screening Rule
NIPS 2022
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference
NIPS 2022
Complexity of Deliberative Coalition Formation
AAAI 2022
Distributed Neural Network Control with Dependability Guarantees: a Compositional Port-Hamiltonian Approach
L4DC 2022
Rate of Convergence of Polynomial Networks to Gaussian Processes
COLT 2022
Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound
NIPS 2022
Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models
L4DC 2022
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior
NIPS 2022
Are All Linear Regions Created Equal?
AISTATS 2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent
NIPS 2022
DALE: Differential Accumulated Local Effects for efficient and accurate global explanations
ACML 2022
Oracle-Efficient Online Learning for Smoothed Adversaries
NIPS 2022
Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach
L4DC 2022
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