Citation Impact
Citing Papers
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
2018 StandoutScienceNobel
Hyperband: a novel bandit-based approach to hyperparameter optimization
2017
Bipartite Ranking through Minimization of Univariate Loss
2011
Boosted Classification Trees and Class Probability/Quantile Estimation
2007
Text Data Augmentation for Deep Learning
2021 Standout
Mastering the game of Go without human knowledge
2017 StandoutNatureNobel
Gradient boosting machines, a tutorial
2013 Standout
Error Analysis of Stochastic Gradient Descent Ranking
2012
An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests.
2009 Standout
Microbial Co-occurrence Relationships in the Human Microbiome
2012 Standout
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
2020 Standout
Trends in extreme learning machines: A review
2014 Standout
Mastering the game of Go with deep neural networks and tree search
2016 StandoutNatureNobel
Extreme learning machine for ranking: Generalization analysis and applications
2014
Taking the Human Out of the Loop: A Review of Bayesian Optimization
2015 Standout
RUSBoost: A Hybrid Approach to Alleviating Class Imbalance
2009 Standout
Convexity, Classification, and Risk Bounds
2006
Learning from Imbalanced Data
2009 Standout
Gaussian Processes for Machine Learning
2005 Standout
MWMOTE--Majority Weighted Minority Oversampling Technique for Imbalanced Data Set Learning
2012 Standout
On Early Stopping in Gradient Descent Learning
2007
Tree-Based Ranking Methods
2009
Boosting for high-dimensional linear models
2006
A Brief Survey of Modern Optimization for Statisticians
2014
A random forest guided tour
2016 Standout
Conceptual Understanding of Convolutional Neural Network- A Deep Learning Approach
2018 Standout
Statistical behavior and consistency of classification methods based on convex risk minimization
2004
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
2010 Standout
Multi-armed bandits with episode context
2011
Understanding deep learning (still) requires rethinking generalization
2021 Standout
On hyperparameter optimization of machine learning algorithms: Theory and practice
2020 Standout
Deep Reinforcement Learning: A Brief Survey
2017 Standout
Recent advances in convolutional neural networks
2017 Standout
Semi-Supervised Learning
2006 Standout
Sure Independence Screening for Ultrahigh Dimensional Feature Space
2008 Standout
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary
2018 Standout
Survey on deep learning with class imbalance
2019 Standout
Regularization and Variable Selection Via the Elastic Net
2005 Standout
A Review on Multi-Label Learning Algorithms
2013 Standout
Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning
2016 Standout
Theory of Classification: a Survey of Some Recent Advances
2005
Works of Nicolas Vayatis being referenced
On the rate of convergence of regularized boosting classifiers
2003
Ranking and Empirical Minimization of U-statistics
2008
Gap-free Bounds for Stochastic Multi-Armed Bandit
2008
Estimation of Simultaneously Sparse and Low Rank Matrices
2012
On the Bayes-risk consistency of regularized boosting methods
2004
Ranking and empirical minimization of U-statistics
2006
Gaussian Process Optimization with Mutual Information
2013