Citation Impact
Citing Papers
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
2018 StandoutScienceNobel
Noise-tolerant instance-based learning algorithms
1989
Dropout: a simple way to prevent neural networks from overfitting
2014 StandoutNobel
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
2010 Standout
Visualizing Data using t-SNE
2008 StandoutNobel
Mining Surprising Patterns Using Temporal Description Length
1998
Learning and representation change
1987
Identifying and eliminating mislabeled training instances
1996
Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions
1997
Improving Regressors using Boosting Techniques
1997
Learning DNF by decision trees
1989
Myths and legends in learning classification rules
1990
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
2019 Standout
Symbolic and Neural Learning Algorithms: An Experimental Comparison
1991
Learning classification trees
1992
Computational pathology: Challenges and promises for tissue analysis
2011
Predicting species distribution: offering more than simple habitat models
2005 Standout
Human-level control through deep reinforcement learning
2015 StandoutNatureNobel
Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
2018 Standout
Machine learning for molecular and materials science
2018 StandoutNature
CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine
2007 Standout
Large language models in medicine
2023 Standout
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
2005 Standout
A Fast Learning Algorithm for Deep Belief Nets
2006 StandoutNobel
Rebuilding community ecology from functional traits
2006 Standout
A survey on deep learning in medical image analysis
2017 Standout
Deep learning and process understanding for data-driven Earth system science
2019 StandoutNature
Deep learning
2015 StandoutNatureNobel
Representation Learning: A Review and New Perspectives
2013 Standout
Neuroscience-Inspired Artificial Intelligence
2017 StandoutNobel
Deep learning in neural networks: An overview
2014 Standout
Simplifying decision trees: A survey
1997
Machine learning: Trends, perspectives, and prospects
2015 StandoutScience
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
2000
Instance‐based prediction of real‐valued attributes
1989
Combining symbolic and neural learning
1994
Model-Based Clustering, Discriminant Analysis, and Density Estimation
2002 Standout
Pattern Recognition and Neural Networks
1996 Standout
Experiments with Incremental Concept Formation: UNIMEM
1987
Theory formation by heuristic search
1983
Pattern Recognition and Machine Learning
2007 Standout
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 Standout
An introduction to ROC analysis
2005 Standout
Bagging Predictors
1996 Standout
Explanation-Based Generalization: A Unifying View
1986
Wrappers for feature subset selection
1997 Standout
Machine Learning in Medicine
2015 Standout
Decision trees and decision-making
1990
Data clustering
1999 Standout
Discussion on the paper by Spiegelhalter, Best, Carlin and van der Linde
2002 Standout
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
2012 StandoutNobel
Maximum entropy modeling of species geographic distributions
2005 Standout
A STRATEGIC METAGAME PLAYER FOR GENERAL CHESS‐LIKE GAMES
1996
Inductive policy: The pragmatics of bias selection
1995
Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
1992
Deep learning for AI
2021 StandoutNobel
An Integration of Rule Induction and Exemplar-Based Learning for Graded Concepts
1995
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
2010 Standout
Instance-Based Learning Algorithms
1991 Standout
Combining Symbolic and Neural Learning
1994
Toward integrating feature selection algorithms for classification and clustering
2005
Acquisition of chess knowledge in AlphaZero
2022 StandoutNobel
Essentials of Artificial Intelligence
1993
Classifier Ensembles with a Random Linear Oracle
2007
Pasting Small Votes for Classification in Large Databases and On-Line
1999
KNOWLEDGE TRANSFER IN DEEP CONVOLUTIONAL NEURAL NETS
2008
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
1998
Learning Deep Architectures for AI
2009 Standout
Evolving Soccer Keepaway Players Through Task Decomposition
2005
Data Mining: Practical Machine Learning Tools and Techniques
2011 Standout
A Survey on Transfer Learning
2009 Standout
Larval Dispersal and Marine Population Connectivity
2008 Standout
Reinforcement learning for the adaptive control of perception and action
1992
A Bayesian Method for the Induction of Probabilistic Networks from Data
1992 Standout
Data mining: concepts and techniques
2012 Standout
Time series forecasting of petroleum production using deep LSTM recurrent networks
2018 Standout
Pruning Decision Trees and Lists
2000
Greedy function approximation: A gradient boosting machine.
2001 Standout
A review of feature selection techniques in bioinformatics
2007 Standout
INSTANCE-B ASED LEARNING: Nearest Neighbour with Generalisation
1995
BOAT—optimistic decision tree construction
1999
Instance-based learning algorithms
1991 Standout
Predictive habitat distribution models in ecology
2000 Standout
Works of Paul E. Utgoff being referenced
Explaining temporal differences to create useful concepts for evaluating states
1990
Randomized Variable Elimination
2002
Learning to control a dynamic physical system
1987
Constructive induction on domain information
1991
Learning Problem-Solving Heuristics Through Practice.
1981
Acquisition of appropriate bias for inductive concept learning
1982
Adjusting bias in concept learning
1983
Multivariate Decision Trees
1995
Goal-directed classification using linear machine decision trees
1994
Perceptron Trees: A Case Study in Hybrid Concept Representations
1989
Decision Tree Induction Based on Efficient Tree Restructuring
1997
Many-Layered Learning
2002
RAPID: Research on Automated Plankton Identification
2007
Machine Learning of Inductive Bias
1986
Incremental Induction of Decision Trees
1989
Learning to control a dynamic physical system
1987
Multivariate decision trees
1995