Nicolas Vayatis
26 papers · 2003–2025 · 6 conferences · across top CS/AI conferences
Achievements
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๐ Conference Polyglot (6) ๐งญ Keyword Pioneer ๐บ๏ธ Taxonomy Completionist (21) ๐ Interdisciplinary Bridge ๐ Academic Marathon (22)
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Keyword Pioneer
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Renaissance Researcher
(7)
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Cross-Pollinator
(5)
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Keyword Trendsetter Combo
(9)
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Grand Slam
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Keyword Champion
(2)
๐ฅ
Unstoppable
(7)
โก
Prolific Year
(5)
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Century Club
(26)
๐๏ธ
Keyword Collector
(84)
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Trend Setter
Conferences
NIPS (8)
JMLR (7)
ICML (5)
AISTATS (4)
AAAI (1)
ICLR (1)
Top co-authors
Research topics
Keywords
roc curve
(6)
link prediction
(3)
graph analysis
(3)
auc optimization
(3)
bipartite ranking
(3)
scoring function
(2)
spectral representation
(2)
proximal method
(2)
graph structure learning
(2)
matrix completion
(2)
autoregressive model
(2)
graph signal
(2)
network analysis
(2)
non-parametric estimation
(2)
spectral radius
(2)
change-point detection
(2)
global optimization
(2)
oracle inequality
(2)
diffusion network
(2)
area under roc curve
(2)
Papers
OneBatchPAM: A Fast and Frugal K-Medoids Algorithm
AAAI 2025
Collaborative likelihood-ratio estimation over graphs
JMLR 2025
Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
JMLR 2025
Collaborative non-parametric two-sample testing
AISTATS 2025
Stein Boltzmann Sampling: A Variational Approach for Global Optimization
AISTATS 2025
Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimization
AISTATS 2024
Discrepancy-Based Active Learning for Domain Adaptation
ICLR 2022
Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation
JMLR 2021
Offline detection of change-points in the mean for stationary graph signals.
AISTATS 2021
Learning the piece-wise constant graph structure of a varying Ising model
ICML 2020
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
ICML 2018
Global optimization of Lipschitz functions
ICML 2017
A ranking approach to global optimization
ICML 2016
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks
NIPS 2015
Gaussian Process Optimization with Mutual Information
ICML 2014
Link Prediction in Graphs with Autoregressive Features
JMLR 2014
Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology
NIPS 2014
Ranking Forests
JMLR 2013
Link Prediction in Graphs with Autoregressive Features
NIPS 2012
Link Discovery using Graph Feature Tracking
NIPS 2010
AUC optimization and the two-sample problem
NIPS 2009
Empirical performance maximization for linear rank statistics
NIPS 2008
On Bootstrapping the ROC Curve
NIPS 2008
Overlaying classifiers: a practical approach for optimal ranking
NIPS 2008
Ranking the Best Instances
JMLR 2007
On the Rate of Convergence of Regularized Boosting Classifiers
JMLR 2003