Brian McWilliams
15 papers · 2013–2025 · 5 venues · across top CS/AI venues
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🗺️ Taxonomy Completionist (42) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
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The Questioner
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Machine Learning
(12)
Optimization & Theory · Machine Learning
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Deep Learning
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Artificial Intelligence
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Core AI
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Mathematics & Optimization
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Computer Vision
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Optimization
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Optimization & Theory · Deep Learning
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Keywords
random projection
(2)
convergence guarantee
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gradient descent
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stochastic gradient descent
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reinforcement learning
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motion estimation
(1)
stochastic gradient
(1)
spectral clustering
(1)
contrastive learning
(1)
principal component analysis
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video segmentation
(1)
video frame interpolation
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robust regression
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feature distribution
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self-supervised learning
(1)
data subsampling
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batch normalization
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evaluation methodology
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out-of-distribution generalization
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semi-supervised learning
(1)
Papers
Live Music Models
NeurIPS 2025
MusicRL: Aligning Music Generation to Human Preferences
ICML 2024
The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium
ICLR 2023
EigenGame Unloaded: When playing games is better than optimizing
ICLR 2022
EigenGame: PCA as a Nash Equilibrium
ICLR 2021
Representation Learning via Invariant Causal Mechanisms
ICLR 2021
PhaseNet for Video Frame Interpolation
CVPR 2018
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks
ICML 2017
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
ICML 2017
A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation
CVPR 2016
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections
AISTATS 2016
Scalable Adaptive Stochastic Optimization Using Random Projections
NeurIPS 2016
Variance Reduced Stochastic Gradient Descent with Neighbors
NeurIPS 2015
Fast and Robust Least Squares Estimation in Corrupted Linear Models
NeurIPS 2014
Correlated random features for fast semi-supervised learning
NeurIPS 2013