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% Types: 0-Thesis, 1-Journal, 2-Conf, 3-TR, 4-Chapter % Subjects: 1-Approx Inf, 2-Sensors, 3-MI, 4-Misc % %DATE-MO|Type|Subj|TAG|TITLE|AUTH|DETAILS|| 2010.07|C27|S01|uai10|Negative Tree-reweighted Belief Propagation|Liu, Ihler|Uncertainty in Artificial Intelligence (UAI), July 2010|| 2010.06|C26|S01|cvpr10|Covering Trees and Lower Bounds on Quadratic Assignment|Yarkony, Fowlkes, Ihler|Computer Vision & Pattern Recognition (CVPR), June 2010|| 2010.05|C25|S01|icml10|Particle Filtered MCMC-MLE with Connections to Contrastive Divergence|Asuncion, Liu, Ihler, Smyth|Int'l Conf on Machine Learning (ICML), June 2010|| 2010.04|C24|S01|aistats10|Learning with Blocks: Composite Likelihood and Contrastive Divergence|Asuncion, Liu, Ihler, Smyth|AI & Statistics (AISTATS), April 2010|| 2010.01 |J9|S05|bioinf10|Estimating Replicate Time-Shifts Using Gaussian Process Regression|Liu, Lin, Anderson, Smyth, Ihler|Bioinformatics 26(6), Mar. 2010, pp. 770-776; doi:10.1093/bioinformatics/btq022||http://bioinformatics.oxfordjournals.org/cgi/reprint/26/6/770

2009.12|C23|S01|nips09|Particle-Based Variational Inference for Continuous Systems|Ihler, Frank, Smyth|Neural Information Processing Systems, Dec. 2009|| 2009.12 |J8|S05|bioinf09|Bayesian detection of non-sinusoidal periodic patterns in circadian expression data|Chudova, Ihler, Lin, Andersen, Smyth|Bioinformatics 25(23), Dec. 2009, pp. 3114-3120; doi: 10.1093/bioinformatics/btp547.||http://bioinformatics.oxfordjournals.org/cgi/reprint/btp547 2009.10 |R4|S01|tr09-06|Bounding Sample Errors in Approximate Distributed Latent Dirichlet Allocation|Ihler, Newman|ICS Technical Report 09-06, Oct. 2009. 2009.09|C22|S20|allerton09|A Low Density Lattice Decoder via Non-parametric Belief Propagation|Bickson, Ihler, Avissar, Dolev|Allerton Conference on Communication, Control, and Computing, Sept. 2009|| 2009.09|C21|S01|ssp09|Adaptive Updates for MAP Configurations with Applications to Bioinformatics|Acar, Ihler, Mettu, Sumer|in IEEE Statistical Signal Processing (SSP), Sept. 2009|| 2009.07 |J7|S05|plos09|Circadian Clock Genes Contribute to the Regulation of Hair Follicle Cycling|Lin, Kumar, Geyfman, Chudova, Ihler, Smyth, Paus, Takahashi, Andersen|PLoS Genetics, 5(7):e1000573. July 2009. doi:10.1371/journal.pgen.1000573||http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000573 2009.04|C20|S01|aistats09|Particle Belief Propagation|Ihler, McAllester|in Twelfth International Conference on Artificial Intelligence and Statistics (AIStats), April 2009.||

2008-09|2|S2|kdsd08|Probabilistic Analysis of a Large Scale Urban Traffic Sensor Data Set|Hutchins, Ihler, Smyth|in Second International Workshop on Knowledge Discovery from Sensor Data 2008.|| 2008-09|2|S1|kdd08|Fast Collapsed Gibbs Sampling for Latent Dirichlet Allocation|Porteous, Newman, Ihler, Asuncion, Smyth, Welling|in ACM Knowledge Discovery and Data Mining (KDD) 2008.|| 2008-07|2|S1|uai08|Adaptive Inference in General Graphical Models|Acar, Ihler, Mettu, Sumer|in Uncertainty in Artificial Intelligence (UAI) 2008.||

2007-12|4|S2|wiley_wsn07|Graphical Models and Fusion in Sensor Networks|Cetin, Chen, Fisher, Ihler, Kreidl, Moses, Wainwright, Williams, Willsky|in Wireless Sensor Networks: Signal Processing and Communications, Wiley 2007.||http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470035579,descCd-tableOfContents.html 2007-12|1|S2|tkdd07|Learning to detect events with Markov-modulated Poisson processes|Ihler, Hutchins, Smyth|ACM Transactions on Knowledge Discovery from Data, Vol 1 Issue 3, Dec. 2007.||http://doi.acm.org/10.1145/1297332.1297337 2007-12|2|S1|nips07|Adaptive Bayesian Inference|Acar, Ihler, Mettu, Sumer|in Neural Information Processing Systems (NIPS) 2007.|| 2007-12|2|S1|camsap07|Modeling Count Data from Multiple Sensors: A Building Occupancy Model|Hutchins, Ihler, Smyth|in Computational Advances in Multisensor Adaptive Processing (CAMSAP) 2007.||

2007-07|2|S1|uai07|Accuracy Bounds for Belief Propagation|Ihler|in Uncertainty in Artificial Intelligence (UAI) 2007.|| 2007-06|1|S1|physd07|Graphical Models for Statistical Inference and Data Assimilation|Ihler, Kirshner, Ghil, Robertson, Smyth|Physica D: Nonlinear Phenomena, June 2007.|Survey of graphical model methods|http://dx.doi.org/10.1016/j.physd.2006.08.023 2006-07|2|S1|uai06|Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation|Porteous, Ihler, Smyth, Welling|in Uncertainty in Artificial Intelligence (UAI) 2006.|| 2005-05|1|S1|jmlr05|Loopy Belief Propagation: Convergence and Effects of Message Errors|Ihler, Fisher, Willsky|Journal of Machine Learning Research, May 2005.|Full version of NIPS'04 paper| 2004-12|2|S1|nips04|Message Errors in Belief Propagation|Ihler, Fisher, Willsky|in Neural Information Processing Systems (NIPS) 2004.|Outstanding Student Paper Award| 2003-06|2|S1|cvpr03|Nonparametric Belief Propagation|Sudderth, Ihler, Freeman, Willsky|in Computer Vision and Pattern Recognition (CVPR) 2003.|also AI Memo # AIM-2002-020| 2003-12|2|S1|nips03|Efficient Multiscale Sampling from Products of Gaussian Mixtures|Ihler, Sudderth, Freeman, Willsky|in Neural Information Processing Systems (NIPS) 2003.|| 2002-08|3|S1|tr2551|Nonparametric Belief Propagation|Sudderth, Ihler, Freeman, Willsky|LIDS Technical Report # 2551, Aug. 2002. % 2006-07|1|S2|spm06|Distributed Fusion in Sensor Networks|Cetin, Chen, Fisher, Ihler, Moses, Wainwright, Willsky|IEEE Signal Processing Magazine, July 2006.|| 2006-08|2|S2|kdd06|Adaptive Event Detection with Time-Varying Poisson Processes|Ihler, Hutchins, Smyth|in Knoweldge Discovery and Data Mining (KDD) 2006.|| 2006-12|2|S2|nips06|Learning Time-Intensity Profiles of Human Activity Using Nonparametric Bayesian Models|Ihler, Smyth|in Neural Information Processing Systems (NIPS) 2006.|| 2005-05|1|S2|jsac05|Nonparametric Belief Propagation for Sensor Network Self-Calibration|Ihler, Fisher, Moses, Willsky|Journal of Selected Areas in Communication, Apr. 2005.|Expanded version of IPSN/ICASSP papers|| 2004-04|2|S2|ipsn04|Nonparametric Belief Propagation for Self-Calibration in Sensor Networks|Ihler, Fisher, Moses, Willsky|in Information Processing in Sensor Networks (IPSN) 2004.|Best Student Paper Award|| 2004-05|2|S2|icassp04|Nonparametric Belief Propagation for Sensor Network Self-Calibration|Ihler, Fisher, Moses, Willsky|in ICASSP 2004.|| 2005-07|2|S2|ssp05|Particle Filtering Under Communications Constraints|Ihler, Fisher, Willsky|in Statistical Signal Processing (SSP) 2005.||

1999-12|2|S3|nips99|Learning Informative Statistics: A Nonparametric Approach|Fisher, Ihler, Viola|in Neural Information Processing Systems (NIPS) 1999.|| 2001-05|2|S3|icassp01|Nonparametric Estimators for Online Signature Authentication|Ihler, Fisher, Willsky|in ICASSP 2001.|| 2003-04|2|S3|ipsn03|Hypothesis Testing over Factorizations for Data Association|Ihler, Fisher, Willsky|in Information Processing in Sensor Networks (IPSN) 2003.|| 2004-08|1|S3|tsp04|Nonparametric Hypothesis Tests for Statistical Dependency|Ihler, Fisher, Willsky|IEEE Transactions on Signal Processing, Aug. 2004.|| 2005-05|2|S3|icassp05|Estimating Dependency and Significance for High-Dimensional Data|Siracusa, Tieu, Ihler, Fisher, Willsky|in ICASSP 2005.|| 2004-06|3|S4|tr2601|Communications-Constrained Inference|Ihler, Fisher, Willsky|LIDS Tech Report 2601|Lossless and lossy encoding of sample-based density estimates|

2005-02|0|S2|ihler_phd|Inference in Sensor Networks: Graphical Models and Particle Methods|Ihler|Ph.D. Thesis, MIT, 2005|| 2000-08|0|S3|ihler_ms|Maximally Informative Subspaces: Nonparametric Estimation for Dynamical Systems|Ihler|Masters' Thesis, MIT, 2000|| 2004-04|0|S4|ihler_area|An Overview of Fast Multipole Methods|Ihler|2004|MIT Area Exam|