Archive of AIRG Presentations

2019
  • 2019/05/01, Ellie Yang

    Classification Algorithms in Modeling Categorical Variables: A Comparison of Multinomial Logistic Regression

    Ellie Yang

  • 2019/04/24, Ron Stewart

    A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications

    Finn Kuusisto, John Steill, Zhaobin Kuang, James Thomson, David Page, Ron Stewart

    AMIA Joint Summits on Translational Science, 2017

  • 2019/04/24, Ron Stewart

    Rediscovering Don Swanson: The Past, Present and Future of Literature-based Discovery

    Neil R. Smalheiser

    Journal of Data and Information Science 2(4), 2017

  • 2019/04/24, Ron Stewart

    BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

    Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova

    arXiv, 2018

  • 2019/04/17, Xiaomin Zhang

    Robust Regression via Hard Thresholding

    Kush Bhatia, Prateek Jain, Purushottam Kar

    NIPS 28, 2015

  • 2019/04/17, Xiaomin Zhang

    Consistent Robust Regression

    Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, Purushottam Kar

    NIPS 30, 2017

  • 2019/04/03, Ankit Pensia

    Bandits With Heavy Tail

    Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi

    IEEE Transactions on Information Theory 59(11), 2013

  • 2019/04/03, Ankit Pensia

    Geometric median and robust estimation in Banach spaces

    Stanislav Minsker

    Bernoulli 21(4), 2015

  • 2019/03/27, David Merrell

    Variational Inference: A Review for Statisticians

    David M. Blei, Alp Kucukelbir, Jon D. McAuliffe

    JASA 112(518), 2017

  • 2019/03/13, Tim Huegerich

    Causal inference in statistics: An overview

    Judea Pearl

    Statistics Surveys 3, 2009

  • 2019/03/06, Matthew Bernstein

    Using deep learning to model the hierarchical structure and function of a cell

    Jianzhu Ma, Michael Ku Yu, Samson Fong, Keiichiro Ono, Eric Sage, Barry Demchak, Roded Sharan, Trey Ideker

    Nature Methods 15, 2018

  • 2019/02/27, Sid Kiblawi

    Deep Neural Networks for YouTube Recommendations

    Paul Covington, Jay Adams, Emre Sargin

    RecSys 10, 2016

  • 2019/02/20, Sathya Ravi

    Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence

    Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh

    AAAI 33, 2019

  • 2019/02/20, Sathya Ravi

    Experimental Design on a Budget for Sparse Linear Models and Applications

    Sathya Narayanan Ravi, Vamsi Ithapu, Sterling Johnson, Vikas Singh

    ICML 33, 2016

  • 2019/02/13, Finn Kuusisto

    The Hanabi Challenge: A New Frontier for AI Research

    Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling

    arXiv, 2019

2018
  • 2018/12/12, David Merrell

    Geometric Deep Learning: Going Beyond Euclidean Data

    Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst

    IEEE Signal Processing Magazine 34(4), 2017

  • 2018/12/12, David Merrell

    Spectral Networks and Locally Connected Networks on Graphs

    Joan Bruna, Wojciech Zaremba, Arthur Szlam, Yann LeCun

    ICLR 2, 2014

  • 2018/12/05, Yunyang Xiong

    Resource-Constrained Neural Network Architecture Search

    Yunyang Xiong, Ronak Mehta, Vikas Singh

    arXive, 2019

  • 2018/11/28, Lucas Morton

    Discovering Structure in High-Dimensional Data Through Correlation Explanation

    Greg Ver Steeg, Aram Galstyan

    NIPS 27, 2014

  • 2018/11/14, Ross Kleiman

    AUCμ: A Performance Metric for Multi-Class Models

    Ross Kleiman, David Page

    ICML 36, 2019

  • 2018/11/07, Xianda (Bryce) Xu

    Binarized Neural Networks

    Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio

    NIPS 29, 2016

  • 2018/10/31, Yuriy Sverchkov

    Anchors: High-Precision Model-Agnostic Explanations

    Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin

    AAAI 32, 2018

  • 2018/10/31, Yuriy Sverchkov

    "Why Should I Trust You?": Explaining the Predictions of Any Classifier

    Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin

    KDD 22, 2016

  • 2018/10/31, Yuriy Sverchkov

    Extracting Tree-Structured Representations of Trained Networks

    Mark Craven, Jude W. Shavlik

    NIPS 8, 1995

  • 2018/10/24, Jinman Zhao

    Generalizing Word Embeddings using Bag of Subwords

    Jinman Zhao, Sidharth Mudgal, Yingyu Liang

    EMNLP, 2018

  • 2018/10/17, Finn Kuusisto

    Learning Dexterous In-Hand Manipulation

    OpenAI: Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, Jonas Schneider, Szymon Sidor, Josh Tobin, Peter Welinder, Lilian Weng, Wojciech Zaremba

    arXiv, 2018

  • 2018/10/10, Collin Engstrom

    Applying family analyses to electronic health records to facilitate genetic research

    Xiayuan Huang, Robert C. Elston, Guilherme J. Rosa, John Mayer, Zhan Ye, Terrie Kitchner, Murray H. Brilliant, David Page, Scott J. Hebbring

    Bioinformatics 34(4), 2018

  • 2018/10/03, Matthew Bernstein

    Bayesian Inference for a Generative Model of Transcriptome Profiles from Single-Cell RNA Sequencing

    Romain Lopez, Jeffrey Regier, Michael B. Cole, Michael I. Jordan, Nir Yosef

    bioRXiv, 2018

  • 2018/09/26, Vishnu Lokhande

    Learning One-Hidden-Layer Neural Networks with Landscape Design

    Rong Ge, Jason D. Lee, Tengyu Ma

    ICLR 6, 2018

  • 2018/09/26, Vishnu Lokhande

    Identifying Generalization Properties in Neural Networks

    Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher

    arXiv, 2018

  • 2018/09/12, Jinman Zhao

    code2vec: Learning Distributed Representations of Code

    Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav

    (to appear) POPL 46, 2019

  • 2018/09/12, Jinman Zhao

    A General Path-Based Representation for Predicting Program Properties

    Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav

    PLDI 39, 2018

  • 2018/05/02, Felipe Gutierrez Barragan

    Matrix capsules with EM routing

    Geoffrey E. Hinton, Sara Sabour, Nicholas Frosst

    ICLR 6, 2018

  • 2018/04/25, Finn Kuusisto

    Hominin skeletal part abundances and claims of deliberate disposal of corpses in the Middle Pleistocene

    Charles P. Egeland, Manuel Domínguez-Rodrigo, Travis Rayne Pickering, Colin G. Menter, Jason L. Heaton

    PNAS 115(18), 2018

  • 2018/04/18, Ross Kleiman

    Cost-Sensitive Multi-class Classification from Probability Estimates

    Deirdre O'Brien, Maya Gupta, and Robert Gray

    ICML 25, 2008

  • 2018/04/11, Jiefeng Chen

    Towards Deep Learning Models Resistant to Adversarial Attacks

    Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu

    ICLR 6, 2018

  • 2018/04/04, Wei Zhang

    RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

    Edward Choi, Mohammad Taha Bahadori, Jimeng Sun, Joshua Kulas, Andy Schuetz, Walter Stewart

    NIPS 29, 2016

  • 2018/03/21, Nikhil Nakhate

    SSD: Single Shot MultiBox Detector

    Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg

    ECCV 14, 2016

  • 2018/03/07, Aubrey Barnard

    Inference via low-dimensional couplings

    Alessio Spantini, Daniele Bigoni, Youssef Marzouk

    arXiv, 2017

  • 2018/02/28, Jinnian Zhang

    PacGAN: The power of two samples in generative adversarial networks

    Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh

    arXiv, 2018

  • 2018/02/21, Jinman Zhao

    Enriching Word Vectors with Subword Information

    Piotr Bojanowski, Edouard Grave, Armand Joulin, Tomas Mikolov

    TACL 5, 2017

  • 2018/02/14, Matthew Bernstein

    Semi-Supervised Prediction-Constrained Topic Models

    Michael Hughes, Gabriel Hope, Leah Weiner, Thomas McCoy, Roy Perlis, Erik Sudderth, Finale Doshi-Velez

    AISTATS 21, 2018

  • 2018/01/31, Xuezhou Zhang

    Training Set Debugging Using Trusted Items

    Xuezhou Zhang, Xiaojin Zhu, Stephen Wright

    AAAI 32, 2018

2017
  • 2017/12/13, Aubrey Barnard

    Mastering the game of Go without human knowledge

    David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, Demis Hassabis

    Nature 550(7676), 2017

  • 2017/12/06, Sathya Ravi

    Gradient Descent Only Converges to Minimizers

    Jason D. Lee, Max Simchowitz, Michael I. Jordan, Benjamin Recht

    COLT 29, 2016

  • 2017/12/06, Sathya Ravi

    Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers

    Jacob Steinhardt, Moses Charikar, Gregory Valiant

    ITCS, 2018

  • 2017/11/29, Matthew Bernstein

    Visualizing Data using t-SNE

    Laurens van der Maaten, Geoffrey Hinton

    JMLR 9, 2008

  • 2017/11/29, Matthew Bernstein

    How to Use t-SNE Effectively

    Martin Wattenberg, Fernanda Viégas, Ian Johnson

    Distill, 2016

  • 2017/11/15, Ayon Sen

    Understanding deep learning requires rethinking generalization

    Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals

    ICLR 5, 2017

  • 2017/11/08, Sumeet Katariya

    Improved Algorithms for Linear Stochastic Bandits

    Yasin Abbasi-Yadkori, Dávid Pál, Csaba Szepesvári

    NIPS 24, 2011

  • 2017/11/01, Ronak Mehta

    Auto-Encoding Variational Bayes

    Diederik P. Kingma, Max Welling

    ICLR 2, 2014

  • 2017/10/25, Tyler Bradshaw

    Machine Learning in Positron Emission Tomography

    Tyler Bradshaw

  • 2017/10/18, Vamsi Ithapu

    Deep Residual Learning for Image Recognition

    Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

    CVPR, 2016

  • 2017/10/18, Vamsi Ithapu

    Densely Connected Convolutional Networks

    Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger

    CVPR, 2017

  • 2017/10/11, Felipe Gutierrez Barragan

    Generative Adversarial Nets

    Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio

    NIPS 27, 2014

  • 2017/10/04, Vamsi Ithapu

    Going Deeper With Convolutions

    Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich

    CVPR, 2015

  • 2017/09/27, Hyunwoo Kim

    Scene Graph Generation by Iterative Message Passing

    Danfei Xu, Yuke Zhu, Christopher B. Choy, Li Fei-Fei

    CVPR, 2017

  • 2017/09/20, Ross Kleiman

    Artificial Intelligence and Life in 2030

    Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David Parkes, William Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller

    One Hundred Year Study on Artificial Intelligence, Stanford University, 2016

  • 2017/05/03, Charles Kuang

    Trace Lasso: A Trace Norm Regularization for Correlated Designs

    Edouard Grave, Guillaume R. Obozinski, Francis R. Bach

    NIPS 24, 2011

  • 2017/04/26, Sid Kiblawi

    Data Programming: Creating Large Training Sets, Quickly

    Alexander J. Ratner, Christopher M. De Sa, Sen Wu, Daniel Selsam, Christopher Ré

    NIPS 29, 2016

  • 2017/04/19, Ara Vartanian

    Wasserstein Generative Adversarial Networks

    Martin Arjovsky, Soumith Chintala, Léon Bottou

    ICML 34, 2017

  • 2017/04/12, Vamsi Ithapu

    Multiresolution Matrix Factorization

    Risi Kondor, Nedelina Teneva, Vikas Garg

    ICML 31, 2014

  • 2017/04/05, Finn Kuusisto

    Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration

    Daniel Lobo, Michael Levin

    PLOS Computational Biology 11(6), 2015

  • 2017/03/29, Hyunwoo Kim

    A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis

    Daniela M. Witten, Robert Tibshirani, Trevor Hastie

    Biostatistics 10(3), 2009

  • 2017/03/08, Akshay Sood

    A Critical Review of Recurrent Neural Networks for Sequence Learning

    Zachary C. Lipton, John Berkowitz, Charles Elkan

    arXiv, 2015

  • 2017/03/01, Ronak Mehta

    Sparse Inverse Covariance Estimation with the Graphical Lasso

    Jerome Friedman, Trevor Hastie, Robert Tibshirani

    Biostatistics 9(3), 2008

  • 2017/02/15, Aubrey Barnard

    Finding Optimal Bayesian Networks

    David Maxwell Chickering, Christopher Meek

    UAI 18, 2002

2011
  • 2011/04/27, Chris Hinrichs

    Maximum Relative Margin and Data-Dependent Regularization

    Pannagadatta K. Shivaswamy, Tony Jebara

    JMLR 11(Feb), 2010

  • 2011/04/13, Andreas Vlachos

    Learning Semantic Correspondences with Less Supervision

    Percy Liang, Michael Jordan, Dan Klein

    International Joint Conference on Natural Language Processing (IJCNLP) 4, 2009

  • 2011/03/30, Kwang-Sun Jun

    Modeling Dyadic Data with Binary Latent Factors

    Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis

    NIPS 19, 2006

  • 2011/03/02, Junming Sui

    When is There a Representer Theorem? Vector Versus Matrix Regularizers

    Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil

    JMLR 10(Nov), 2009

2010
  • 2010/12/08, Andreas Vlachos

    A Multi-Pass Sieve for Coreference Resolution

    Karthik Raghunathan, Heeyoung Lee, Sudarshan Rangarajan, Nate Chambers, Mihai Surdeanu, Dan Jurafsky, Christopher Manning

    Empirical Methods in Natural Language Processing (EMNLP), 2010

  • 2010/11/10, Bryan Gibson

    PAC Generalization Bounds for Co-training

    Sanjoy Dasgupta, Michael L. Littman, David A. McAllester

    NIPS 14, 2001

  • 2010/10/27, Debbie Chasman

    Occam's Two Razors: The Sharp and the Blunt

    Pedro Domingos

    KDD 4, 1998

  • 2010/10/13, Suhail Shergill

    Structured Ranking Learning using Cumulative Distribution Networks

    Jim C. Huang, Brendan J. Frey

    NIPS 21, 2008

  • 2010/09/29, Chris Hinrichs

    Proximal Methods for Sparse Hierarchical Dictionary Learning

    Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis Bach

    ICML 27, 2010

  • 2010/04/07, Suhail Shergill

    Bayesian Algorithms for Causal Data Mining

    Subramani Mani, Constantin F. Aliferis, Alexander Statnikov

    NIPS 2008 Workshop on Causality PMLR 6, 2010

  • 2010/03/24, Ameet Soni

    Model Selection: Beyond the Bayesian/Frequentist Divide

    Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin Cawley

    JMLR 11(Jan), 2010

  • 2010/03/10, Andrew Goldberg

    Semi-Supervised Sequence Modeling with Syntactic Topic Models

    Wei Li, Andrew McCallum

    AAAI 20, 25

  • 2010/02/24, Kwang-Sun Jun

    Dynamic Non-Parametric Mixture Models and The Recurrent Chinese Restaurant Process: with Applications to Evolutionary Clustering

    Amr Ahmed, Eric Xing

    SDM 8, 2008

  • 2010/02/10, Bryan Gibson

    DUOL: A Double Updating Approach for Online Learning

    Peilin Zhao, Steven C. Hoi, Rong Jin

    NIPS 22, 2009

2009
  • 2009/11/11, Ameet Soni

    Supervised Learning from Multiple Experts: Whom to trust when everyone lies a bit

    Vikas Raykar, Shipeng Yu, Linda Zhao, Anna Jerebko, Charles Florin, Gerardo Valadez, Luca Bogoni, Linda Moy

    ICML 26, 2009

  • 2009/10/28, Kendrick Boyd

    Learning Markov Logic Network Structure via Hypergraph Lifting

    Stanley Kok, Pedro Domingos

    ICML 26, 2009

  • 2009/10/14, Chris Hinrichs

    Let the Kernel Figure it Out; Principled Learning of Pre-Processing for Kernel Classifiers

    Peter Vincent Gehler, Sebastian Nowozin

    CVPR, 2009

  • 2009/09/30, Debbie Chasman

    Uncertainty Sampling and Transductive Experimental Design for Active Dual Supervision

    Vikas Sindhwani, Prem Melville, Richard Lawrence

    ICML 26, 2009

  • 2009/09/16, Junming Sui

    On the Relation Between Multi-Instance Learning and Semi-Supervised Learning

    Zhi-Hua Zhou, Jun-Ming Xu

    ICML 24, 2007

  • 2009/04/22, Lisa Torrey

    Learning Classifiers from Only Positive and Unlabeled Data

    Charles Elkan, Keith Noto

    KDD 14, 2008

  • 2009/04/08, Hidayath Ansari

    Clustering with Local and Global Regularization

    Fei Wang, Changshui Zhang, Tao Li

    AAAI 22, 2007

  • 2009/04/01, David Andrzejewski

    Training Products of Experts by Minimizing Contrastive Divergence

    Geoffrey E. Hinton

    Neural Computation 14(8), 2002

  • 2009/03/11, Chris Hinrichs

    Robust Support Vector Machine Training via Convex Outlier Ablation

    Linli Xu, Koby Crammer, Dale Schuurmans

    AAAI 21, 2006

  • 2009/03/04, Nate Fillmore

    The Tradeoffs of Large Scale Learning

    Léon Bottou, Olivier Bousquet

    NIPS 20, 2007

  • 2009/02/18, Andrew Goldberg

    Large Scale Manifold Transduction

    Michael Karlen, Jason Weston, Ayse Erkan, Ronan Collobert

    ICML 25, 2008

  • 2009/02/04, Gautam Kunapuli

    Model Selection via Bilevel Optimization

    Kristin P. Bennett, Jing Hu, Gautam Kunapuli, Jong-Shi Pang

    International Joint Conference on Neural Networks, 2006

2008
  • 2008/11/24, Bess Berg

    Boosted Bayesian network classifiers

    Yushi Jing, Vladimir Pavlović, James M. Rehg

    Machine Learning 73(2), 2008

  • 2008/11/10, Andrew Goldberg

    A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning

    Ronan Collobert, Jason Weston

    ICML 25, 2008

  • 2008/10/13, Burr Settles

    Learning from Labeled Features using Generalized Expectation Criteria

    Gregory Druck, Gideon Mann, Andrew McCallum

    SIGIR 31, 2008

  • 2008/09/29, David Andrzejewski

    Beam Sampling for the Infinite Hidden Markov Model

    Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, and Zoubin Ghahramani

    ICML 25, 2008

  • 2008/09/15, Eric Lantz

    SVM Optimization: Inverse Dependence on Training Set Size

    Shai Shalev-Shwartz, Nathan Srebro

    ICML 25, 2008

  • 2008/05/07, Louis Oliphant

    Predicting Good Probabilities with Supervised Learning

    Alexandru Niculescu-Mizil, Rich Caruana

    ICML 22, 2005

  • 2008/04/30, David Andrzejewski

    Non-redundant clustering with conditional ensembles

    David Gondek, Thomas Hofmann

    KDD 11, 2005

  • 2008/04/09, Lisa Torrey

    WebCrow: A Web-Based System for Crossword Solving

    Marco Ernandes, Giovanni Angelini, Marco Gori

    AAAI 20, 2005

  • 2008/03/26, Ted Wild

    Online Bayes Point Machines

    Edward Harrington, Ralf Herbrich, Jyrki Kivinen, John Platt, Robert C. Williamson

    Pacific-Asia Conference on Knowledge Discovery and Data Mining (PACKDD) 7, 2003

  • 2008/03/05, Sriraam Natarajan

    Online Passive-Aggressive Algorithms

    Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer

    NIPS 16, 2003

  • 2008/02/20, Ted Wild

    Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels

    Olvi L. Mangasarian, Edward W. Wild, Glenn M. Fung

    TKDD 2(3), 2008

  • 2008/02/20, Ted Wild

    Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels

    Olvi L. Mangasarian, Edward W. Wild

    UW-Madison Data Mining Institute Technical Reports, 2007

  • 2008/02/13, Héctor Corrada Bravo

    Colored Maximum Variance Unfolding

    Le Song, Arthur Gretton, Karsten Borgwardt, Alex J. Smola

    NIPS 20, 2007

2007
  • 2007/12/10, Chris Hinrichs

    Spatial Latent Dirichlet Allocation

    Xiaogang Wang, Eric Grimson

    NIPS 20, 2007

  • 2007/11/26, Louis Oliphant

    Searching for Interacting Features

    Zheng Zhao, Huan Liu

    IJCAI 20, 2007

  • 2007/11/12, Lisa Torrey

    Transfer Learning in Real-Time Strategy Games Using Hybrid CBR / RL

    Manu Sharma, Michael Holmes, Juan Santamaria, Arya Irani, Charles Isbell, Ashwin Ram

    IJCAI 20, 2007

  • 2007/11/05, David Andrzejewski

    Nonparametric Bayes Pachinko Allocation

    Wei Li, David Blei, Andrew McCallum

    UAI 23, 2007

  • 2007/10/15, Andrew Goldberg

    Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification

    John Blitzer, Mark Dredze, Fernando Pereira

    ACL 45, 2007

  • 2007/10/01, Héctor Corrada Bravo

    Convex optimization techniques for fitting sparse Gaussian graphical models

    Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont, Georges Natsoulis

    ICML 23, 2006

  • 2007/09/17, Ted Wild

    Model selection for support vector machines via uniform design

    Chien-Ming Huang, Yuh-Jye Lee, Dennis K. J. Lin, Su-Yun Huang

    Computational Statistics & Data Analysis 52(1), 2007

  • 2007/03/14, Ted Wild

    Rule extraction from linear support vector machines

    Glenn Fung, Sathyakama Sandilya, R. Bharat Rao

    KDD 11, 2005

  • 2007/02/14, Lisa Torrey

    Relating reinforcement learning performance to classification performance

    John Langford, Bianca Zadrozny

    ICML 22, 2005

  • 2007/01/31, Louis Oliphant

    On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes

    Andrew Y. Ng, Michael I. Jordan

    NIPS 14, 2001

  • 2007/01/31, Louis Oliphant

    Classification with Hybrid Generative / Discriminative Models

    Rajat Raina, Yirong Shen, Andrew McCallum, Andrew Y. Ng

    NIPS 16, 2003

2006
  • 2006/12/13, Ameet Soni

    CONTRAfold: RNA secondary structure prediction without physics-based models

    Chuong B. Do, Daniel A. Woods, Serafim Batzoglou

    Bioinformatics 22(14), 2006

  • 2006/11/29, Jurgen Van Gael

    Gaussian Processes for Machine Learning: Chapter 2: Regression

    Carl Edward Rasmussen, Christopher K. I. Williams

    MIT Press, 2006

  • 2006/11/15, Adam Smith

    Multiple Alignment of Continuous Time Series

    Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Andrew Emili

    NIPS 17, 2004

  • 2006/11/01, Trevor Walker

    Predictive State Representations: A New Theory for Modeling Dynamical Systems

    Satinder Singh, Michael James, Matthew Rudary

    UAI 20, 2004

  • 2006/10/18, Ted Wild

    Choosing Between Two Learning Algorithms Based on Calibrated Tests

    Remco R. Bouckaert

    ICML 20, 2003

  • 2006/10/04, Louis Oliphant

    A Taxonomy of Global Optimization Methods Based on Response Surfaces

    Donald R. Jones

    Journal of Global Optimization 21(4), 2001

  • 2006/09/25, Frank DiMaio

    Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs of Arbitrary Topology

    Firas Hamze, Nando de Freitas

    NIPS 18, 2005

  • 2006/08/30, Mark Goadrich

    Cost curves: An improved method for visualizing classifier performance

    Chris Drummond, Robert C. Holte

    Machine Learning 65(1), 2006

  • 2006/08/16, Jurgen Van Gael

    Topic Modeling: Beyond Bag-of-Words

    Hanna M. Wallach

    ICML 23, 2006

  • 2006/08/16, Jurgen Van Gael

    Latent Dirichlet Allocation

    David M. Blei, Andrew Y. Ng, and Michael I. Jordan

    JMLR 3, 2003

  • 2006/07/19, David Andrzejewski

    Hierarchical Topic Models and the Nested Chinese Restaurant Process

    Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum, David M. Blei

    NIPS 16, 2003

  • 2006/07/05, Ted Wild

    Generalized Approximate Cross Validation for Support Vector Machines, or, Another Way to Look at Margin-Like Quantities

    Grace Wahba, Yi Lin, Hao Zhang

    Advances in Large Margin Classifiers, MIT Press, 2000

  • 2006/06/21, Lisa Torrey

    Exploiting Task Relatedness for Multiple Task Learning

    Shai Ben-DavidReba Schuller

    COLT 16, 2003

  • 2006/06/07, Keith Noto

    Evolving the Structure of Hidden Markov Models

    Kyoung-Jae Won, Adam Prügel-Bennett, Anders Krogh

    IEEE Transactions on Evolutionary Computation 10(1), 2006

  • 2006/05/24, Frank DiMaio

    Generalized Belief Propagation

    Jonathan S. Yedidia, William T. Freeman, Yair Weiss

    NIPS 13, 2000

  • 2006/05/05, Keith Noto

    Being Bayesian about Network Structure

    Nir Friedman, Daphne Koller

    UAI 16, 2000

  • 2006/04/21, Louis Oliphant

    Probabilistic Reasoning with Hierarchically Structured Variables

    Rita Sharma, David Poole

    IJCAI 19, 2005

  • 2006/04/07, Trevor Walker

    Recent Advances in Hierarchical Reinforcement Learning

    Andrew G. Barto, Sridhar Mahadevan

    Discrete Event Dynamic Systems 13(4), 2003

  • 2006/03/24, Jesse Davis

    Combining Top-down and Bottom-up Techniques in Inductive Logic Programming

    John M. Zelle, Raymond J. Mooney, Joshua B. Konvisser

    ICML 11, 1994

  • 2006/03/24, Jesse Davis

    Machine Invention of First-Order Predicates by Inverting Resolution

    Stephen Muggleton, Wray Buntine

    ICML 5, 1988

  • 2006/03/10, Pradheep Elango

    A Survey of Kernels for Structured Data

    Thomas Gärtner

    SIGKDD Explorations 5(1), 2003

  • 2006/02/24

    Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars

    Luke Zettlemoyer, Michael Collins

    UAI 21, 2005

  • 2006/02/06, Ted Wild

    Statistical Comparisons of Classifiers over Multiple Data Sets

    Janez Demšar

    JMLR 7, 2006

2005
  • 2005/12/07, Ted Wild

    Latent Dirichlet Allocation

    David M. Blei, Andrew Y. Ng, and Michael I. Jordan

    JMLR 3, 2003

  • 2005/11/30, Héctor Corrada Bravo

    Markov Logic Networks

    Matthew Richardson, Pedro Domingos

    Machine Learning 62(1-2), 2005

  • 2005/11/09, Ted Wild

    The Entire Regularization Path for the Support Vector Machine

    Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu

    NIPS 17, 2004

  • 2005/10/26, Lisa Torrey

    Relational Instance Based Regression for Relational Reinforcement Learning

    Kurt Driessens, Jan Ramon

    ICML 20, 2003

  • 2005/10/12, Jerry Zhu

    Graph Kernels by Spectral Transforms

    Xiaojin Zhu, Jaz Kandola, John Lafferty, Zoubin Ghahramani

    Semi-Supervised Learning, MIT Press, 2006

2003
  • 2003/12/04, Beverly Seavy

    Learning from Cluster Examples

    Toshihiro Kamishima, Fumio Motoyoshi

    Machine Learning 53(3), 2003

  • 2003/11/20, Michael Shultz

    Finding Motifs Using Random Projections

    Jeremy Buhler, Martin Tompa

    Journal of Computational Biology 9(2), 2002

  • 2003/11/20, Michael Shultz

    Genome-scale approaches to resolving incongruence in molecular phylogenies

    Antonis Rokas, Barry L. Williams, Nicole King, Sean B. Carroll

    Nature 425(6960), 2003

  • 2003/11/06, Louis Oliphant

    Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming

    Mary Elaine Califf, Raymond J. Mooney

    New Generation Computing 16(3), 1998

  • 2003/10/30, Michael Waddell

    Human-Machine Collaborative Planning

    James Allen, George Ferguson

    International NASA Workshop on Planning and Scheduling for Space 3, 2002

  • 2003/10/16, Mark Goadrich

    Scaling Up ILP to Large Examples: Results on Link Discovery for Counter-Terrorism

    Lappoon R. Tang, Raymond J. Mooney, Prem Melville

    KDD Workshop on Multi-Relational Data Mining (MRDM), 2003

  • 2003/10/02, Soumya Ray

    Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm

    Nick Littlestone

    Machine Learning 2(4), 1988

2002
  • 2002/12/06, Glenn Fung

    Transductive Inference for Text Classification using Support Vector Machines

    Thorsten Joachims

    ICML 16, 1999

  • 2002/11/22, Michael Molla

    Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis

    Hagit Shatkay, Stephen Edwards, W. John Wilbur, Mark Boguski

    ISMB 8, 2000

  • 2002/11/08, Sean McIlwain

    A Sequence-Profile-Based HMM for Predicting and Discriminating β Barrel Membrane Proteins

    Pier Luigi Martelli, Piero Fariselli, Anders Krogh, Rita Casadio

    Bioinformatics 18, 2002

  • 2002/10/25, Frank DiMaio

    A Study of Two Probabilistic Methods for Searching Large Spaces with ILP

    Ashwin Srinivasan

    1999

  • 2002/10/11, Mark Rich

    Boosted Wrapper Induction

    Dayne Freitag, Nicholas Kushmerick

    AAAI 17, 2000

  • 2002/09/27, Louis Oliphant

    Data Perturbation for Escaping Local Maxima in Learning

    Gal Elidan, Matan Ninio, Nir Friedman, Dale Shuurmans

    AAAI 18, 2002

  • 2002/09/13, Soumya Ray

    Boosting the Margin: A New Explanation for the Effectiveness of Voting Methods

    Robert E. Shapire, Yoav Freund, Peter Bartlett, Wee Sun Lee

    Annals of Statistics 26, 1998

  • 2002/04/26, Joe Bockhorst

    Exploiting Generative Models in Discriminative Classifiers

    Tommi Jaakkola, David Haussler

    NIPS 11, 1998

  • 2002/04/26, Joe Bockhorst

    A Discriminative Framework for Detecting Remote Protein Homologies

    Tommi Jaakkola, Mark Diekhans, David Haussler

    Journal of Computational Biology 7, 2000

  • 2002/04/12, Darryl Roy

    The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances

    Marco Dorigo, Thomas Stützle

    Handbook of Metaheuristics 57, International Series in Operations Research, 2003

  • 2002/03/15, Glenn Fung

    A Tutorial on Support Vector Machines for Pattern Recognition

    Christopher J. C. Burges

    Data Mining and Knowledge Discovery 2, 1998

  • 2002/03/01, Irene Ong

    Feature Construction with Version Spaces for Biochemical Applications

    Stefan Kramer, Luc De Raedt

    ICML 18, 2001

  • 2002/03/01, Irene Ong

    Feature Selection for High-Dimensional Genomic Microarray Data

    Eric P. Xing, Michael I. Jordan, Richard M. Karp

    ICML 18, 2001

  • 2002/02/15, Mark Rich

    Stochastic Logic Programs

    Stephen Muggleton

    Advances in Inductive Logic Programming, IOS Press, 1996

  • 2002/02/15, Mark Rich

    Learning Stochastic Logic Programs

    Stephen Muggleton

    AAAI Technical Report WS-00-06, 2000

  • 2002/02/01, Marios Skounakis

    Global Training of Document Processing Systems using Graph Transformer Networks

    Léon Bottou, Yoshua Bengio, Yann Le Cun

    CVPR, 1997

Generated from the archive data.