| 2017 | RECOMB | A Flow Procedure for the Linearization of Genome Sequence Graphs. | David Haussler, Maciej Smuga-Otto, Benedict Paten, Adam M. Novak, Sergei Nikitin, Maria Zueva, Dmitrii Miagkov |
| 2014 | RECOMB | Building a Pangenome Reference for a Population. | Ngan Nguyen, Glenn Hickey, Daniel R. Zerbino, Brian J. Raney, Dent Earl, Joel Armstrong, David Haussler, Benedict Paten |
| 2011 | KDD | Cancer genomics. | David Haussler |
| 2010 | RECOMB | Cactus Graphs for Genome Comparisons. | Benedict Paten, Mark Diekhans, Dent Earl, John St. John, Jian Ma, Bernard B. Suh, David Haussler |
| 2008 | STOC | Computing how we became human. | David Haussler |
| 2007 | RECOMB | A Heuristic Algorithm for Reconstructing Ancestral Gene Orders with Duplications. | Jian Ma, Aakrosh Ratan, Louxin Zhang, Webb Miller, David Haussler |
| 2006 | RECOMB | Detecting the Dependent Evolution of Biosequences. | Jeremy Darot, Chen-Hsiang Yeang, David Haussler |
| 2006 | RECOMB | Ultraconserved Elements, Living Fossil Transposons, and Rapid Bursts of Change: Reconstructing the Uneven Evolutionary History of the Human Genome. | David Haussler |
| 2006 | RECOMB | New Methods for Detecting Lineage-Specific Selection. | Adam C. Siepel, Katherine S. Pollard, David Haussler |
| 2004 | ISMB | Into the heart of darkness: large-scale clustering of human non-coding DNA. | Gill Bejerano, David Haussler, Mathieu Blanchette |
| 2004 | ISMB | Efficient approximations for learning phylogenetic HMM models from data. | Vladimir Jojic, Nebojsa Jojic, Christopher Meek, Dan Geiger, Adam C. Siepel, David Haussler, David Heckerman |
| 2004 | PSB | Transcriptome and Genome Conservation of Alternative Splicing Events in Humans and Mice. | Charles W. Sugnet, W. James Kent, Manuel Ares, David Haussler |
| 2004 | RECOMB | Computational identification of evolutionarily conserved exons. | Adam C. Siepel, David Haussler |
| 2003 | ISMB | Gene structure-based splice variant deconvolution using a microarry platform. | Hui Wang, Earl Hubbell, Jing-Shan Hu, Gangwu Mei, Melissa S. Cline, Gang Lu, Tyson Clark, Michael A. Siani-Rose, Manuel Ares, David Kulp, David Haussler |
| 2003 | RECOMB | Computational analysis of the human and other mammalian genomes. | David Haussler |
| 2003 | RECOMB | Scoring two-species local alignments to try to statistically separate neutrally evolving from selected DNA segments. | Krishna M. Roskin, Mark Diekhans, David Haussler |
| 2003 | RECOMB | Combining phylogenetic and hidden Markov models in biosequence analysis. | Adam C. Siepel, David Haussler |
| 2001 | PSB | Promoter Region-Based Classification of Genes. | Paul Pavlidis, Terrence S. Furey, M. Liberto, David Haussler, William Noble Grundy |
| 1999 | AISTATS | Probabilistic kernel regression models. | Tommi S. Jaakkola, David Haussler |
| 1999 | ISMB | Using the Fisher Kernel Method to Detect Remote Protein Homologies. | Tommi S. Jaakkola, Mark Diekhans, David Haussler |
| 1999 | PSB | A Probabilistic Approach to a Consensus Multiple Alignment. | Betty Lazareva-Ulitsky, David Haussler |
| 1997 | COLT | A Brief Look at Some Machine Learning Problems in Genomics. | David Haussler |
| 1997 | RECOMB | Improved splice site detection in Genie. | Martin G. Reese, Frank H. Eeckman, David Kulp, David Haussler |
| 1996 | ISMB | A Generalized Hidden Markov Model for the Recognition of Human Genes in DNA. | David Kulp, David Haussler, Martin G. Reese, Frank H. Eeckman |
| 1996 | KDD | KDD for Science Data Analysis: Issues and Examples. | Usama M. Fayyad, David Haussler, Paul E. Stolorz |
| 1995 | COLT | General Bounds on the Mutual Information Between a Parameter and | David Haussler, Manfred Opper |
| 1994 | COLT | Rigorous Learning Curve Bounds from Statistical Mechanics. | David Haussler, H. Sebastian Seung, Michael J. Kearns, Naftali Tishby |
| 1994 | CPM | Recent Methods for RNA Modeling Using Stochastic Context-Free Grammars. | Yasubumi Sakakibara, Michael Brown, Richard Hughey, I. Saira Mian, Kimmen Sjlander, Rebecca C. Underwood, David Haussler |
| 1994 | ISMB | RNA Modeling Using Gibbs Sampling and Stochastic Context Free Grammars. | Leslie Grate, Mark Herbster, Richard Hughey, David Haussler, I. Saira Mian, Harry Noller |
| 1994 | ISMB | Optimally Parsing a Sequence into Different Classes Based on Multiple Types of Evidence. | Gary D. Stormo, David Haussler |
| 1993 | FOCS | Scale-sensitive Dimensions, Uniform Convergence, and Learnability | Noga Alon, Shai Ben-David, Nicol Cesa-Bianchi, David Haussler |
| 1993 | ISMB | Using Dirichlet Mixture Priors to Derive Hidden Markov Models for Protein Families. | Michael Brown, Richard Hughey, Anders Krogh, I. Saira Mian, Kimmen Sjlander, David Haussler |
| 1993 | STOC | How to use expert advice. | Nicol Cesa-Bianchi, Yoav Freund, David P. Helmbold, David Haussler, Robert E. Schapire, Manfred K. Warmuth |
| 1991 | COLT | Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension. | David Haussler, Michael J. Kearns, Robert E. Schapire |
| 1991 | COLT | Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron With Noise. | Manfred Opper, David Haussler |
| 1990 | AAAI | Probably Approximately Correct Learning. | David Haussler |
| 1990 | ALT | Decision Theoretic Generalizations of the PAC Learning Model. | David Haussler |
| 1989 | COLT | Informed Parsimonious Inference of Prototypical Genetic Sequences. | Aleksandar Milosavljevic, David Haussler, Jerzy Jurka |
| 1989 | FOCS | Generalizing the PAC Model: Sample Size Bounds From Metric Dimension-based Uniform Convergence Results | David Haussler |
| 1989 | ICML | Two Algorithms That Learn DNF by Discovering Relevant Features. | Giulia Pagallo, David Haussler |
| 1988 | COLT | Learning Decision Trees from Random Examples. | Andrzej Ehrenfeucht, David Haussler |
| 1988 | COLT | A General Lower Bound on the Number of Examples Needed for Learning. | Andrzej Ehrenfeucht, David Haussler, Michael J. Kearns, Leslie G. Valiant |
| 1988 | COLT | Equivalence of Models for Polynomial Learnability. | David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth |
| 1988 | COLT | Predicting {0, 1}-Functions on Randomly Drawn Points. | David Haussler, Nick Littlestone, Manfred K. Warmuth |
| 1988 | FOCS | Predicting {0,1}-Functions on Randomly Drawn Points (Extended Abstract) | David Haussler, Nick Littlestone, Manfred K. Warmuth |
| 1987 | AAAI | Learning Conjunctive Concepts in Structural Domains. | David Haussler |
| 1986 | AAAI | Quantifying the Inductive Bias in Concept Learning (Extended Abstract). | David Haussler |
| 1986 | STOC | Classifying Learnable Geometric Concepts with the Vapnik-Chervonenkis Dimension (Extended Abstract) | Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth |
| 1985 | ICALP | On Total Regulators Generated by Derivation Relations. | Walter Bucher, Andrzej Ehrenfeucht, David Haussler |
| 1985 | ICALP | Applications of an Infinite Squarefree CO-CFL. | Michael G. Main, Walter Bucher, David Haussler |
| 1984 | ICALP | Building the Minimal DFA for the Set of all Subwords of a Word On-line in Linear Time. | Anselm Blumer, J. Blumer, Andrzej Ehrenfeucht, David Haussler, Ross M. McConnell |
| 1984 | STOC | Building a Complete Inverted File for a Set of Text Files in Linear Time | Anselm Blumer, J. Blumer, Andrzej Ehrenfeucht, David Haussler, Ross M. McConnell |
| 1982 | ICALP | Conditions Enforcing Regularity of Context-Free Languages. | Andrzej Ehrenfeucht, David Haussler, Grzegorz Rozenberg |