about me Hal Daumé III
about me cv + bio publications research teaching students software photos calendar contact me links		I am Hal Daume III, an Assistant Professor in Computer Science at the U of Utah (CV). My research is in machine learning (primarily Bayesian methods and structured prediction), natural language processing and computational biology. More thoughts on these fields are on my blog. Recent publications: Semi-supervised or Semi-unsupervised? [HD] (SSLNLP 2009) Bayesian Hierarchical Multitask Learning [HD] (UAI 2009) Unsupervised Search-based Structured Pred [HD] (ICML 2009) Exponential Family Hybrid Learning [AA,HD] (IJCAI09) One-pass SVMs [PR,HD,SV] (IJCAI09) Bayesian Areal Linguistics [HD] (NAACL09) Streaming NLP: Language Modeling [AG,HD,SV] (NAACL09) Search-based Structured Prediction [HD,JL,DM] (MLJ09) Bayesian Coarse Graining [PL,QS,HD,GV] (J Chem Phys,09) Perceptron-based Coherence Prediction [DG,HD,JC] (ICSA08) Infinite Hierarchical Factor Regression [PR,HD] (NIPS08) Cross-Task Self Training [HD] (EMNLP08) Trading Structure for Features [PL,HD,DK] (ICML08) Name Transliteration in SMT [UH,KK,HD] (ACL08) Office: MEB 3126 Phone: 801-585-3586 Recent software: HBC to simulate and compile Bayesian models (updated 03 Apr 2008) WhatToSee to find research papers relevant to your interests (updated 09 May 2007) MegaM for training maximum entropy and perceptron models (updated 08 Oct 07) DPSearch for fast DP inference (updated 20 Dec 06) TagChunk for POS tagging, shallow parsing and NER (updated 11 Oct 08) FastDT for training boosted and bagged decision trees (updated 05 Sep 06) Recent teaching: Topics in ML: TBD     CS 7941     (Fall   2009) Machine Learning     CS 5350/6350     (Fall   2009) Topics in ML: Recent results     CS 7941     (Summer  2009) Artificial Intelligence     CS 5300/6300     (Spring  2009) Topics in ML: Learning Theory     CS 7941     (Spring  2009) Machine Learning     CS 5350/6350     (Fall   2008) Topics in ML: Graphical Models     CS 7941     (Fall   2008) Topics in ML: Multitask Learning     CS 7941     (Summer  2008) Machine Learning     CS 5350/6350     (Spring  2008) Topics in ML: Kernel Methods     CS 7941     (Spring  2008) Applications of Natural Language Processing     CS 5964/6964     (Fall   2007) Topics in ML: Manifold Learning     CS 7941     (Summer  2008) Machine Learning     CS 5350/6350     (Spring  2007) Students: Prospective students: Read this and email me after taking machine learning and/or NLP about potential research. Current students: Arvind Agarwal (PhD), Scott Alfeld (BS), Amit Goyal (PhD), Piyush Rai (PhD). Upcoming conferences: (bold = plan to attend): Location Due Date Notification Conference Dates NIPS 08 Vancouver Past TBA 08-13 Dec 08 SODA 09 New York Past TBA 04-06 Jan 09 EACL 09 Athens Past Past 30 Mar-03 Apr 09 AISTATS 09 Florida Past Past 16-19 Apr 09 RECOMB 09 Tuscon Past Past 18-21 May 09 NAACL-HLT 09 Boulder Past Past 31 May-05 Jun 09 CONLL 09 Boulder Past 03 Apr 09 04-05 Jun 09 ICML 09 Montreal Past 06 Apr 09 15-19 Jun 09 UAI 09 Montreal Past 13 Apr 09 19-21 Jun 09 SIGIR 09 Boston Past 11 Apr 09 19-23 Jun 09 CVPR 09 Florida Past TBA 19-26 Jun 09 COLT 09 Montreal Past 24 Apr 09 20-23 Jun 09 ISMB 09 Stockholm Past 27 Mar 09 27 Jun-02 Jul 09 KDD 09 Paris Past 10 Apr 09 28 Jun-01 Jul 09 IJCAI 09 Pasadena Past 31 Mar 09 11-17 Jul 09 ACL 09 Singapore Past 12 Apr 09 02-07 Aug 09 EMNLP 09 Singapore 01 May 09 01 Jun 09 06-07 Aug 09 ICCV 09 Beijing Past TBA 27 Sep-04 Oct 09 PSB 10 Hawaii 13 July 09 09 Oct 09 04-08 Jan 10 COLING 10 Beijing 19 Apr 10 28 May 10 23-27 Aug 10
quick links    nlp blog    searn    nlp/ml meeting    ml (cs5350)    ai (cs5300)    anlp (cs5964)    mlrg (cs7941)    algo (cs7936)    whattosee    thesis    jmlr    haskell tutorial conferences    nips 08    soda 09    eacl 09    aistats 09    recomb 09    naacl-hlt 09    conll 09    icml 09    uai 09    sigir 09    cvpr 09    colt 09    ismb 09    kdd 09    ijcai 09    acl 09    emnlp 09    iccv 09    psb 10    coling 10
last updated on twenty seven june, two thousand nine; contact