Mikhail Bilenko

发表

Scaling up machine learning: parallel and distributed approaches

John Langford, Ron Bekkerman, Mikhail Bilenko, 2011, KDD '11 Tutorials.

Adaptive duplicate detection using learnable string similarity measures

Raymond J. Mooney, Mikhail Bilenko, R. Mooney, 2003, KDD '03.

Selection of Negative Samples for One-class Matrix Factorization

Chih-Jen Lin, Hsiang-Fu Yu, Mikhail Bilenko, 2017, SDM.

A probabilistic framework for semi-supervised clustering

Raymond J. Mooney, Sugato Basu, Mikhail Bilenko, 2004, KDD.

Machine Learning at Microsoft with ML.NET

Yiwen Zhu, Markus Weimer, Matteo Interlandi, 2019, KDD.

Adaptive Name Matching in Information Integration

Pradeep Ravikumar, Stephen E. Fienberg, William W. Cohen, 2003, IEEE Intell. Syst..

Scaling up machine learning: parallel and distributed approaches

John Langford, Ron Bekkerman, Mikhail Bilenko, 2011, KDD '11 Tutorials.

Scaling Up Machine Learning: Supervised and Unsupervised Learning Algorithms

John Langford, Ron Bekkerman, Mikhail Bilenko, 2011 .

Predictive client-side profiles for personalized advertising

Matthew Richardson, Mikhail Bilenko, Matthew Richardson, 2011, KDD.

Scaling Up Machine Learning: Frameworks for Scaling Up Machine Learning

John Langford, Ron Bekkerman, Mikhail Bilenko, 2011 .

Employing Trainable String Similarity Metrics for Information Integration

Raymond J. Mooney, Mikhail Bilenko, 2003, IIWeb.

Scaling up Machine Learning

Ron Bekkerman, Mikhail Bilenko, John Langford, 2011 .

Scaling Up Machine Learning: Alternative Learning Settings

John Langford, Ron Bekkerman, Mikhail Bilenko, 2011 .

Scaling Up Machine Learning: Contributors

Ron Bekkerman, Mikhail Bilenko, John Langford, 2011 .

Probabilistic Semi-Supervised Clustering with Constraints

Arindam Banerjee, Raymond J. Mooney, Sugato Basu, 2006, Semi-Supervised Learning.

Intelligent information acquisition for improved clustering

Maytal Saar-Tsechansky, Prem Melville, Mikhail Bilenko, 2007 .

Studying the use of popular destinations to enhance web search interaction

Ryen W. White, Silviu Cucerzan, Mikhail Bilenko, 2007, SIGIR.

Ryen W. White, Silviu Cucerzan, Mikhail Bilenko, 2008, TWEB.

Adaptive product normalization: using online learning for record linkage in comparison shopping

Sugato Basu, Mikhail Bilenko, Mehran Sahami, 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

Enhancing web search by promoting multiple search engine use

Ryen W. White, Matthew Richardson, Allison P. Heath, 2008, SIGIR '08.

Tutorial summary: Machine learning in IR: recent successes and new opportunities

Paul N. Bennett, Kevyn Collins-Thompson, Mikhail Bilenko, 2009, ICML '09.

Mining the search trails of surfing crowds: identifying relevant websites from user activity

Ryen W. White, Mikhail Bilenko, M. Bilenko, 2008, WWW.

Fast Prediction of New Feature Utility pdf

Mikhail Bilenko, Hoyt A. Koepke, H. Koepke, 2012, ICML.

Catching the drift: learning broad matches from clickthrough data

Matthew Richardson, Sonal Gupta, Mikhail Bilenko, 2009, KDD.

Targeted, Not Tracked: Client-Side Solutions for Privacy-Friendly Behavioral Advertising

Matthew Richardson, Janice Y. Tsai, Mikhail Bilenko, 2011 .

Mikhail Bilenko, M. Bilenko, 2004, AAAI.

Lazy Paired Hyper-Parameter Tuning

Mikhail Bilenko, Alice X. Zheng, M. Bilenko, 2013, IJCAI.

Scaling Up Stochastic Dual Coordinate Ascent

Lin Xiao, Thomas Finley, Mikhail Bilenko, 2015, KDD.

Scaling Up Machine Learning: Scaling Up Machine Learning: Introduction

John Langford, Ron Bekkerman, Mikhail Bilenko, 2011 .

Talking the talk vs. walking the walk: salience of information needs in querying vs. browsing

Ryen W. White, Matthew Richardson, Mikhail Bilenko, 2008, SIGIR '08.

Crypto-Nets: Neural Networks over Encrypted Data pdf

Pengtao Xie, Michael Naehrig, Kristin E. Lauter, 2014, ArXiv.

Scaling Up Machine Learning: Preface

John Langford, Ron Bekkerman, Mikhail Bilenko, 2011 .

Adaptive Blocking: Learning to Scale Up Record Linkage

Raymond J. Mooney, Mikhail Bilenko, Beena Kamath, 2006, Sixth International Conference on Data Mining (ICDM'06).

Integrating constraints and metric learning in semi-supervised clustering

Raymond J. Mooney, Sugato Basu, Mikhail Bilenko, 2004, ICML.

Predictive Client-side Profiles for Keyword Advertising

Matthew Richardson, Mikhail Bilenko, M. Bilenko, 2016 .

Information retrieval and advertising

Yi Zhang, Matthew Richardson, Evgeniy Gabrilovich, 2009, SIGF.

Time Adaptive Sketches (Ada-Sketches) for Summarizing Data Streams

Arnd Christian König, Anshumali Shrivastava, Mikhail Bilenko, 2016, SIGMOD Conference.

Towards Production-Grade, Platform-Independent Distributed ML

Markus Weimer, Mikhail Bilenko, Dhruv Mahajan, 2016 .

Active Information Acquisition for Improved Clustering

Prem Melville, Mikhail Bilenko, M. Bilenko, 2007 .

Axiomatic Analysis of Co-occurrence Similarity Functions

Christos Faloutsos, Mikhail Bilenko, Dengyong Zhou, 2012 .