Archive of AIRG Presentations
- 2019
-
-
2019/05/01, Ellie Yang
Classification Algorithms in Modeling Categorical Variables: A Comparison of Multinomial Logistic Regression
-
2019/04/24, Ron Stewart
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications
AMIA Joint Summits on Translational Science, 2017
-
2019/04/24, Ron Stewart
Rediscovering Don Swanson: The Past, Present and Future of Literature-based Discovery
Journal of Data and Information Science 2(4), 2017
-
2019/04/24, Ron Stewart
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
arXiv, 2018
-
2019/04/17, Xiaomin Zhang
Robust Regression via Hard Thresholding
NIPS 28, 2015
-
2019/04/17, Xiaomin Zhang
Consistent Robust Regression
NIPS 30, 2017
-
2019/04/03, Ankit Pensia
Bandits With Heavy Tail
IEEE Transactions on Information Theory 59(11), 2013
-
2019/04/03, Ankit Pensia
Geometric median and robust estimation in Banach spaces
Bernoulli 21(4), 2015
-
2019/03/27, David Merrell
Variational Inference: A Review for Statisticians
JASA 112(518), 2017
-
2019/03/13, Tim Huegerich
Causal inference in statistics: An overview
Statistics Surveys 3, 2009
-
2019/03/06, Matthew Bernstein
Using deep learning to model the hierarchical structure and function of a cell
Nature Methods 15, 2018
-
2019/02/27, Sid Kiblawi
Deep Neural Networks for YouTube Recommendations
RecSys 10, 2016
-
2019/02/20, Sathya Ravi
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence
AAAI 33, 2019
-
2019/02/20, Sathya Ravi
Experimental Design on a Budget for Sparse Linear Models and Applications
ICML 33, 2016
-
2019/02/13, Finn Kuusisto
The Hanabi Challenge: A New Frontier for AI Research
arXiv, 2019
arxiv: toc meta pdf | info: research platform board game
-
- 2018
-
-
2018/12/12, David Merrell
Geometric Deep Learning: Going Beyond Euclidean Data
IEEE Signal Processing Magazine 34(4), 2017
-
2018/12/12, David Merrell
Spectral Networks and Locally Connected Networks on Graphs
ICLR 2, 2014
-
2018/12/05, Yunyang Xiong
Resource-Constrained Neural Network Architecture Search
arXive, 2019
-
2018/11/28, Lucas Morton
Discovering Structure in High-Dimensional Data Through Correlation Explanation
NIPS 27, 2014
-
2018/11/14, Ross Kleiman
AUCμ: A Performance Metric for Multi-Class Models
ICML 36, 2019
-
2018/11/07, Xianda (Bryce) Xu
Binarized Neural Networks
NIPS 29, 2016
-
2018/10/31, Yuriy Sverchkov
Anchors: High-Precision Model-Agnostic Explanations
AAAI 32, 2018
-
2018/10/31, Yuriy Sverchkov
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
KDD 22, 2016
-
2018/10/31, Yuriy Sverchkov
Extracting Tree-Structured Representations of Trained Networks
NIPS 8, 1995
-
2018/10/24, Jinman Zhao
Generalizing Word Embeddings using Bag of Subwords
EMNLP, 2018
-
2018/10/17, Finn Kuusisto
Learning Dexterous In-Hand Manipulation
arXiv, 2018
-
2018/10/10, Collin Engstrom
Applying family analyses to electronic health records to facilitate genetic research
Bioinformatics 34(4), 2018
-
2018/10/03, Matthew Bernstein
Bayesian Inference for a Generative Model of Transcriptome Profiles from Single-Cell RNA Sequencing
bioRXiv, 2018
-
2018/09/26, Vishnu Lokhande
Learning One-Hidden-Layer Neural Networks with Landscape Design
ICLR 6, 2018
-
2018/09/26, Vishnu Lokhande
Identifying Generalization Properties in Neural Networks
arXiv, 2018
-
2018/09/12, Jinman Zhao
code2vec: Learning Distributed Representations of Code
(to appear) POPL 46, 2019
-
2018/09/12, Jinman Zhao
A General Path-Based Representation for Predicting Program Properties
PLDI 39, 2018
-
2018/05/02, Felipe Gutierrez Barragan
Matrix capsules with EM routing
ICLR 6, 2018
-
2018/04/25, Finn Kuusisto
Hominin skeletal part abundances and claims of deliberate disposal of corpses in the Middle Pleistocene
PNAS 115(18), 2018
-
2018/04/18, Ross Kleiman
Cost-Sensitive Multi-class Classification from Probability Estimates
ICML 25, 2008
-
2018/04/11, Jiefeng Chen
Towards Deep Learning Models Resistant to Adversarial Attacks
ICLR 6, 2018
-
2018/04/04, Wei Zhang
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism
NIPS 29, 2016
-
2018/03/21, Nikhil Nakhate
SSD: Single Shot MultiBox Detector
ECCV 14, 2016
-
2018/03/07, Aubrey Barnard
Inference via low-dimensional couplings
arXiv, 2017
-
2018/02/28, Jinnian Zhang
PacGAN: The power of two samples in generative adversarial networks
arXiv, 2018
-
2018/02/21, Jinman Zhao
Enriching Word Vectors with Subword Information
TACL 5, 2017
-
2018/02/14, Matthew Bernstein
Semi-Supervised Prediction-Constrained Topic Models
AISTATS 21, 2018
-
2018/01/31, Xuezhou Zhang
Training Set Debugging Using Trusted Items
AAAI 32, 2018
-
- 2017
-
-
2017/12/13, Aubrey Barnard
Mastering the game of Go without human knowledge
Nature 550(7676), 2017
-
2017/12/06, Sathya Ravi
Gradient Descent Only Converges to Minimizers
COLT 29, 2016
-
2017/12/06, Sathya Ravi
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers
ITCS, 2018
-
2017/11/29, Matthew Bernstein
Visualizing Data using t-SNE
JMLR 9, 2008
-
2017/11/29, Matthew Bernstein
How to Use t-SNE Effectively
Distill, 2016
-
2017/11/15, Ayon Sen
Understanding deep learning requires rethinking generalization
ICLR 5, 2017
-
2017/11/08, Sumeet Katariya
Improved Algorithms for Linear Stochastic Bandits
NIPS 24, 2011
-
2017/11/01, Ronak Mehta
Auto-Encoding Variational Bayes
ICLR 2, 2014
-
2017/10/25, Tyler Bradshaw
Machine Learning in Positron Emission Tomography
info: bio
-
2017/10/18, Vamsi Ithapu
Deep Residual Learning for Image Recognition
CVPR, 2016
-
2017/10/18, Vamsi Ithapu
Densely Connected Convolutional Networks
CVPR, 2017
-
2017/10/11, Felipe Gutierrez Barragan
Generative Adversarial Nets
NIPS 27, 2014
-
2017/10/04, Vamsi Ithapu
Going Deeper With Convolutions
CVPR, 2015
-
2017/09/27, Hyunwoo Kim
Scene Graph Generation by Iterative Message Passing
CVPR, 2017
-
2017/09/20, Ross Kleiman
Artificial Intelligence and Life in 2030
One Hundred Year Study on Artificial Intelligence, Stanford University, 2016
-
2017/05/03, Charles Kuang
Trace Lasso: A Trace Norm Regularization for Correlated Designs
NIPS 24, 2011
-
2017/04/26, Sid Kiblawi
Data Programming: Creating Large Training Sets, Quickly
NIPS 29, 2016
-
2017/04/19, Ara Vartanian
Wasserstein Generative Adversarial Networks
ICML 34, 2017
-
2017/04/12, Vamsi Ithapu
Multiresolution Matrix Factorization
ICML 31, 2014
-
2017/04/05, Finn Kuusisto
Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration
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
Biostatistics 10(3), 2009
-
2017/03/08, Akshay Sood
A Critical Review of Recurrent Neural Networks for Sequence Learning
arXiv, 2015
-
2017/03/01, Ronak Mehta
Sparse Inverse Covariance Estimation with the Graphical Lasso
Biostatistics 9(3), 2008
-
2017/02/15, Aubrey Barnard
Finding Optimal Bayesian Networks
UAI 18, 2002
-
- 2011
-
-
2011/04/27, Chris Hinrichs
Maximum Relative Margin and Data-Dependent Regularization
JMLR 11(Feb), 2010
-
2011/04/13, Andreas Vlachos
Learning Semantic Correspondences with Less Supervision
International Joint Conference on Natural Language Processing (IJCNLP) 4, 2009
-
2011/03/30, Kwang-Sun Jun
Modeling Dyadic Data with Binary Latent Factors
NIPS 19, 2006
-
2011/03/02, Junming Sui
When is There a Representer Theorem? Vector Versus Matrix Regularizers
JMLR 10(Nov), 2009
-
- 2010
-
-
2010/12/08, Andreas Vlachos
A Multi-Pass Sieve for Coreference Resolution
Empirical Methods in Natural Language Processing (EMNLP), 2010
-
2010/11/10, Bryan Gibson
PAC Generalization Bounds for Co-training
NIPS 14, 2001
-
2010/10/27, Debbie Chasman
Occam's Two Razors: The Sharp and the Blunt
KDD 4, 1998
-
2010/10/13, Suhail Shergill
Structured Ranking Learning using Cumulative Distribution Networks
NIPS 21, 2008
-
2010/09/29, Chris Hinrichs
Proximal Methods for Sparse Hierarchical Dictionary Learning
ICML 27, 2010
-
2010/04/07, Suhail Shergill
Bayesian Algorithms for Causal Data Mining
NIPS 2008 Workshop on Causality PMLR 6, 2010
-
2010/03/24, Ameet Soni
Model Selection: Beyond the Bayesian/Frequentist Divide
JMLR 11(Jan), 2010
-
2010/03/10, Andrew Goldberg
Semi-Supervised Sequence Modeling with Syntactic Topic Models
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
SDM 8, 2008
-
2010/02/10, Bryan Gibson
DUOL: A Double Updating Approach for Online Learning
NIPS 22, 2009
-
- 2009
-
-
2009/11/11, Ameet Soni
Supervised Learning from Multiple Experts: Whom to trust when everyone lies a bit
ICML 26, 2009
-
2009/10/28, Kendrick Boyd
Learning Markov Logic Network Structure via Hypergraph Lifting
ICML 26, 2009
-
2009/10/14, Chris Hinrichs
Let the Kernel Figure it Out; Principled Learning of Pre-Processing for Kernel Classifiers
CVPR, 2009
-
2009/09/30, Debbie Chasman
Uncertainty Sampling and Transductive Experimental Design for Active Dual Supervision
ICML 26, 2009
-
2009/09/16, Junming Sui
On the Relation Between Multi-Instance Learning and Semi-Supervised Learning
ICML 24, 2007
-
2009/04/22, Lisa Torrey
Learning Classifiers from Only Positive and Unlabeled Data
KDD 14, 2008
-
2009/04/08, Hidayath Ansari
Clustering with Local and Global Regularization
AAAI 22, 2007
-
2009/04/01, David Andrzejewski
Training Products of Experts by Minimizing Contrastive Divergence
Neural Computation 14(8), 2002
-
2009/03/11, Chris Hinrichs
Robust Support Vector Machine Training via Convex Outlier Ablation
AAAI 21, 2006
-
2009/03/04, Nate Fillmore
The Tradeoffs of Large Scale Learning
NIPS 20, 2007
-
2009/02/18, Andrew Goldberg
Large Scale Manifold Transduction
ICML 25, 2008
-
2009/02/04, Gautam Kunapuli
Model Selection via Bilevel Optimization
International Joint Conference on Neural Networks, 2006
-
- 2008
-
-
2008/11/24, Bess Berg
Boosted Bayesian network classifiers
Machine Learning 73(2), 2008
-
2008/11/10, Andrew Goldberg
A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning
ICML 25, 2008
-
2008/10/13, Burr Settles
Learning from Labeled Features using Generalized Expectation Criteria
SIGIR 31, 2008
-
2008/09/29, David Andrzejewski
Beam Sampling for the Infinite Hidden Markov Model
ICML 25, 2008
-
2008/09/15, Eric Lantz
SVM Optimization: Inverse Dependence on Training Set Size
ICML 25, 2008
-
2008/05/07, Louis Oliphant
Predicting Good Probabilities with Supervised Learning
ICML 22, 2005
-
2008/04/30, David Andrzejewski
Non-redundant clustering with conditional ensembles
KDD 11, 2005
-
2008/04/09, Lisa Torrey
WebCrow: A Web-Based System for Crossword Solving
AAAI 20, 2005
-
2008/03/26, Ted Wild
Online Bayes Point Machines
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PACKDD) 7, 2003
-
2008/03/05, Sriraam Natarajan
Online Passive-Aggressive Algorithms
NIPS 16, 2003
-
2008/02/20, Ted Wild
Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels
TKDD 2(3), 2008
-
2008/02/20, Ted Wild
Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels
UW-Madison Data Mining Institute Technical Reports, 2007
-
2008/02/13, Héctor Corrada Bravo
Colored Maximum Variance Unfolding
NIPS 20, 2007
-
- 2007
-
-
2007/12/10, Chris Hinrichs
Spatial Latent Dirichlet Allocation
NIPS 20, 2007
-
2007/11/26, Louis Oliphant
Searching for Interacting Features
IJCAI 20, 2007
-
2007/11/12, Lisa Torrey
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR / RL
IJCAI 20, 2007
-
2007/11/05, David Andrzejewski
Nonparametric Bayes Pachinko Allocation
UAI 23, 2007
-
2007/10/15, Andrew Goldberg
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification
ACL 45, 2007
-
2007/10/01, Héctor Corrada Bravo
Convex optimization techniques for fitting sparse Gaussian graphical models
ICML 23, 2006
-
2007/09/17, Ted Wild
Model selection for support vector machines via uniform design
Computational Statistics & Data Analysis 52(1), 2007
-
2007/03/14, Ted Wild
Rule extraction from linear support vector machines
KDD 11, 2005
-
2007/02/14, Lisa Torrey
Relating reinforcement learning performance to classification performance
ICML 22, 2005
-
2007/01/31, Louis Oliphant
On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes
NIPS 14, 2001
-
2007/01/31, Louis Oliphant
Classification with Hybrid Generative / Discriminative Models
NIPS 16, 2003
-
- 2006
-
-
2006/12/13, Ameet Soni
CONTRAfold: RNA secondary structure prediction without physics-based models
Bioinformatics 22(14), 2006
-
2006/11/29, Jurgen Van Gael
Gaussian Processes for Machine Learning: Chapter 2: Regression
MIT Press, 2006
-
2006/11/15, Adam Smith
Multiple Alignment of Continuous Time Series
NIPS 17, 2004
-
2006/11/01, Trevor Walker
Predictive State Representations: A New Theory for Modeling Dynamical Systems
UAI 20, 2004
-
2006/10/18, Ted Wild
Choosing Between Two Learning Algorithms Based on Calibrated Tests
ICML 20, 2003
-
2006/10/04, Louis Oliphant
A Taxonomy of Global Optimization Methods Based on Response Surfaces
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
NIPS 18, 2005
-
2006/08/30, Mark Goadrich
Cost curves: An improved method for visualizing classifier performance
Machine Learning 65(1), 2006
-
2006/08/16, Jurgen Van Gael
Topic Modeling: Beyond Bag-of-Words
ICML 23, 2006
-
2006/08/16, Jurgen Van Gael
Latent Dirichlet Allocation
JMLR 3, 2003
-
2006/07/19, David Andrzejewski
Hierarchical Topic Models and the Nested Chinese Restaurant Process
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
Advances in Large Margin Classifiers, MIT Press, 2000
-
2006/06/21, Lisa Torrey
Exploiting Task Relatedness for Multiple Task Learning
COLT 16, 2003
-
2006/06/07, Keith Noto
Evolving the Structure of Hidden Markov Models
IEEE Transactions on Evolutionary Computation 10(1), 2006
-
2006/05/24, Frank DiMaio
Generalized Belief Propagation
NIPS 13, 2000
-
2006/05/05, Keith Noto
Being Bayesian about Network Structure
UAI 16, 2000
-
2006/04/21, Louis Oliphant
Probabilistic Reasoning with Hierarchically Structured Variables
IJCAI 19, 2005
-
2006/04/07, Trevor Walker
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems 13(4), 2003
-
2006/03/24, Jesse Davis
Combining Top-down and Bottom-up Techniques in Inductive Logic Programming
ICML 11, 1994
author: pdf
-
2006/03/24, Jesse Davis
Machine Invention of First-Order Predicates by Inverting Resolution
ICML 5, 1988
author: pdf
-
2006/03/10, Pradheep Elango
A Survey of Kernels for Structured Data
SIGKDD Explorations 5(1), 2003
-
2006/02/24
Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars
UAI 21, 2005
-
2006/02/06, Ted Wild
Statistical Comparisons of Classifiers over Multiple Data Sets
JMLR 7, 2006
-
- 2005
-
-
2005/12/07, Ted Wild
Latent Dirichlet Allocation
JMLR 3, 2003
-
2005/11/30, Héctor Corrada Bravo
Markov Logic Networks
Machine Learning 62(1-2), 2005
-
2005/11/09, Ted Wild
The Entire Regularization Path for the Support Vector Machine
NIPS 17, 2004
-
2005/10/26, Lisa Torrey
Relational Instance Based Regression for Relational Reinforcement Learning
ICML 20, 2003
-
2005/10/12, Jerry Zhu
Graph Kernels by Spectral Transforms
Semi-Supervised Learning, MIT Press, 2006
-
- 2003
-
-
2003/12/04, Beverly Seavy
Learning from Cluster Examples
Machine Learning 53(3), 2003
-
2003/11/20, Michael Shultz
Finding Motifs Using Random Projections
Journal of Computational Biology 9(2), 2002
-
2003/11/20, Michael Shultz
Genome-scale approaches to resolving incongruence in molecular phylogenies
Nature 425(6960), 2003
-
2003/11/06, Louis Oliphant
Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming
New Generation Computing 16(3), 1998
-
2003/10/30, Michael Waddell
Human-Machine Collaborative Planning
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
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
Machine Learning 2(4), 1988
-
- 2002
-
-
2002/12/06, Glenn Fung
Transductive Inference for Text Classification using Support Vector Machines
ICML 16, 1999
-
2002/11/22, Michael Molla
Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis
ISMB 8, 2000
-
2002/11/08, Sean McIlwain
A Sequence-Profile-Based HMM for Predicting and Discriminating β Barrel Membrane Proteins
Bioinformatics 18, 2002
-
2002/10/25, Frank DiMaio
A Study of Two Probabilistic Methods for Searching Large Spaces with ILP
1999
-
2002/10/11, Mark Rich
Boosted Wrapper Induction
AAAI 17, 2000
-
2002/09/27, Louis Oliphant
Data Perturbation for Escaping Local Maxima in Learning
AAAI 18, 2002
-
2002/09/13, Soumya Ray
Boosting the Margin: A New Explanation for the Effectiveness of Voting Methods
Annals of Statistics 26, 1998
-
2002/04/26, Joe Bockhorst
Exploiting Generative Models in Discriminative Classifiers
NIPS 11, 1998
-
2002/04/26, Joe Bockhorst
A Discriminative Framework for Detecting Remote Protein Homologies
Journal of Computational Biology 7, 2000
venue: meta
-
2002/04/12, Darryl Roy
The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances
Handbook of Metaheuristics 57, International Series in Operations Research, 2003
venue: meta
-
2002/03/15, Glenn Fung
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery 2, 1998
venue: meta
-
2002/03/01, Irene Ong
Feature Construction with Version Spaces for Biochemical Applications
ICML 18, 2001
-
2002/03/01, Irene Ong
Feature Selection for High-Dimensional Genomic Microarray Data
ICML 18, 2001
venue: meta
-
2002/02/15, Mark Rich
Stochastic Logic Programs
Advances in Inductive Logic Programming, IOS Press, 1996
-
2002/02/15, Mark Rich
Learning Stochastic Logic Programs
AAAI Technical Report WS-00-06, 2000
-
2002/02/01, Marios Skounakis
Global Training of Document Processing Systems using Graph Transformer Networks
CVPR, 1997
-
Generated from the archive data.