classification error
- North America > United States > California > Los Angeles County > Pasadena (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Europe > Greece (0.04)
Persistent Test-time Adaptation in Recurring Testing Scenarios
Current test-time adaptation (TT A) approaches aim to adapt a machine learning model to environments that change continuously.
- North America > United States > Illinois (0.04)
- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
- North America > United States > New Jersey > Mercer County > Princeton (0.04)
- (3 more...)
- Information Technology (0.92)
- Health & Medicine (0.92)
- North America > United States (0.28)
- South America > Chile > Santiago Metropolitan Region > Santiago Province > Santiago (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Europe > Spain > Basque Country (0.04)
- Workflow (0.49)
- Research Report (0.46)
- Leisure & Entertainment (0.46)
- Government > Regional Government (0.46)
Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
We present a comprehensive study of surrogate loss functions for learning to defer.
- North America > United States > Massachusetts > Middlesex County > Cambridge (0.05)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- North America > Canada > Quebec > Montreal (0.04)
- (3 more...)
Nonzero-sum Adversarial Hypothesis Testing Games
Sarath Yasodharan, Patrick Loiseau
Neural Information Processing Systems http://nips.cc/
- Information Technology > Security & Privacy (0.93)
- Leisure & Entertainment > Games (0.68)
Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond Taiji Suzuki 1,2, Denny Wu
Langevin dynamics (MFLD) (Mei et al., 2018; Hu et al., 2019) is particularly attractive due to the MFLD arises from a noisy gradient descent update on the parameters, where Gaussian noise is injected to the gradient to encourage "exploration". Furthermore, uniform-in-time estimates of the particle discretization error have also been established (Suzuki et al., The goal of this work is to address the following question.
- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
- Africa > Middle East > Tunisia > Ben Arous Governorate > Ben Arous (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- (3 more...)
Estimating Learnability in the Sublinear Data Regime
Neural Information Processing Systems http://nips.cc/
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- Africa > Sudan (0.04)
- North America > Canada > Quebec > Montreal (0.04)
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs
Pedro Mercado, Francesco Tudisco, Matthias Hein
Neural Information Processing Systems http://nips.cc/
- North America > United States > Texas (0.04)
- North America > Canada (0.04)
- Europe > Italy (0.04)
- Europe > Germany > Baden-Württemberg > Tübingen Region > Tübingen (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- North America > Canada (0.04)