Citation Impact
Citing Papers
Content-boosted collaborative filtering for improved recommendations
2002
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
2004
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
2010 Standout
Boosting the margin: A new explanation for the effectiveness of voting methods
1997
Evaluation Measures for Models Assessment over Imbalanced Data Sets
2013
Kernel Methods for Deep Learning
2009
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
2006 Standout
Business Intelligence and Analytics: From Big Data to Big Impact
2012 Standout
State-of-the-art in artificial neural network applications: A survey
2018 Standout
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
2020 Standout
Extreme Learning Machine for Regression and Multiclass Classification
2011 Standout
Random Forests
2001 Standout
Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)
2000 Standout
Incorporating contextual information in recommender systems using a multidimensional approach
2005
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
2020 Standout
Convexity, Classification, and Risk Bounds
2006
Learning from Imbalanced Data
2009 Standout
LIFT: A new framework of learning from testing data for face recognition
2010
Extreme learning machine: Theory and applications
2006 Standout
Boosting the margin: a new explanation for the effectiveness of voting methods
1998 Standout
Semi-Supervised Learning Literature Survey
2005 Standout
Community detection in graphs
2009 Standout
Top 10 algorithms in data mining
2007 Standout
A tutorial on support vector regression
2004 Standout
Gaussian Processes for Machine Learning
2005 Standout
Cost-sensitive boosting for classification of imbalanced data
2007 Standout
MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets
2009 Standout
From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
2009 Standout
Estimating the Support of a High-Dimensional Distribution
2001 Standout
A mean field view of the landscape of two-layer neural networks
2018
The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network
1998
Prediction Games and Arcing Algorithms
1999
Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions
2011 Standout
Ensemble of keyword extraction methods and classifiers in text classification
2016 Standout
Classifying text streams by keywords using classifier ensemble
2011
Active Dual Collaborative Filtering with Both Item and Attribute Feedback
2011
Text classification without negative examples revisit
2006
Robust Real-Time Face Detection
2004 Standout
Statistical pattern recognition: a review
2000 Standout
Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations
2010
Probabilistic Principal Component Analysis
1999 Standout
On combining classifiers
1998 Standout
Least angle regression
2004 Standout
Recommender systems survey
2013 Standout
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
2010 Standout
Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda
2019 Standout
A survey on semi-supervised learning
2019 Standout
Understanding deep learning (still) requires rethinking generalization
2021 Standout
On hyperparameter optimization of machine learning algorithms: Theory and practice
2020 Standout
Physics-informed machine learning
2021 Standout
A Survey of Deep Active Learning
2021 Standout
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
1998 Standout
Collaborative Filtering beyond the User-Item Matrix
2014 Standout
Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction
2006 Standout
Data Mining: Practical Machine Learning Tools and Techniques
2011 Standout
Textual aggregation approaches in OLAP context: A survey
2017
Sure Independence Screening for Ultrahigh Dimensional Feature Space
2008 Standout
On the mathematical foundations of learning
2001
A Survey on Transfer Learning
2009 Standout
Improved Boosting Algorithms Using Confidence-rated Predictions
1999 Standout
Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
2005 Standout
A survey on feature selection methods
2013 Standout
Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data
2002 Standout
New Support Vector Algorithms
2000 Standout
A survey on concept drift adaptation
2014 Standout
Greedy function approximation: A gradient boosting machine.
2001 Standout
Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators
2001
Approximation and learning by greedy algorithms
2008
A Roadmap of Agent Research and Development
1998 Standout
Works of Wee Sun Lee being referenced
Generalization in Decision Trees and DNF: Does Size Matter?
1997
Text classification by labeling words
2004
Collaborative Learning and Recommender Systems
2001
Optimizing classifier performance in word sense disambiguation by redefining word sense classes
2007
Validating Co-Training Models for Web Image Classification
2005
Learning classifiers without negative examples: A reduction approach
2008
The importance of convexity in learning with squared loss
1998
Importance sampling for online planning under uncertainty
2018
Learning with positive and unlabeled examples using weighted logistic regression
2003
Efficient agnostic learning of neural networks with bounded fan-in
1996