MLSP-P3: Learning Theory and Models III |
Session Type: Poster |
Time: Wednesday, March 17, 16:00 - 18:00 |
Location: Poster Area E |
Session Chair: Jose Principe, University of Florida, Gainesville |
MLSP-P3.1: LEARNING ALPHA-INTEGRATION WITH PARTIALLY-LABELED DATA |
Heeyoul Choi; Texas A&M University |
Seungjin Choi; Pohang University of Science and Technology |
Anup Katake; Starvision Technologies |
Yoonsuck Choe; Texas A&M University |
MLSP-P3.2: KERNEL WIDTH ADAPTATION IN INFORMATION THEORETIC COST FUNCTIONS |
Abhishek Singh; University of Florida |
Jose Principe; University of Florida |
MLSP-P3.3: A CONDITIONAL DISTRIBUTION FUNCTION BASED APPROACH TO DESIGN NONPARAMETRIC TESTS OF INDEPENDENCE AND CONDITIONAL INDEPENDENCE |
Sohan Seth; University of Florida |
Jose Principe; University of Florida |
MLSP-P3.4: A CLOSED FORM RECURSIVE SOLUTION FOR MAXIMUM CORRENTROPY TRAINING |
Abhishek Singh; University of Florida |
Jose Principe; University of Florida |
MLSP-P3.5: THEORETICAL ANALYSES FOR A CLASS OF KERNELS WITH AN INVARIANT METRIC |
Akira Tanaka; Hokkaido University |
Masaaki Miyakoshi; Hokkaido University |
MLSP-P3.6: MESSAGE ERROR ANALYSIS OF LOOPY BELIEF PROPAGATION |
Xiangqiong Shi; University of Illinois at Chicago |
Dan Schonfeld; University of Illinois at Chicago |
Daniela Tuninetti; University of Illinois at Chicago |
MLSP-P3.7: EXPECTATION PROPAGATION FOR ESTIMATING THE PARAMETERS OF THE BETA DISTRIBUTION |
Zhanyu Ma; KTH - Royal Institute of Technology |
Arne Leijon; KTH - Royal Institute of Technology |
MLSP-P3.8: VARIATIONAL BAYESIAN INFERENCE FOR POINT PROCESS GENERALIZED LINEAR MODELS IN NEURAL SPIKE TRAINS ANALYSIS |
Zhe Chen; MIT/MGH/HMS |
Fabian Kloosterman; Massachusetts Institute of Technology |
Matthew A. Wilson; Massachusetts Institute of Technology |
Emery N. Brown; MIT/MGH/HMS |
MLSP-P3.9: A NONPARAMETRIC BAYESIAN MODEL FOR KERNEL MATRIX COMPLETION |
John Paisley; Duke Universtiy |
Lawrence Carin; Duke Universtiy |
MLSP-P3.10: EVIDENCE-BASED CUSTOM-PRECISION ESTIMATION WITH APPLICATIONS TO SOLVING NONLINEAR APPROXIMATION PROBLEMS |
Dmitriy Shutin; Graz University of Technology |
Manfred Muecke; University of Vienna |
MLSP-P3.11: VARIATIONAL NONPARAMETRIC BAYESIAN HIDDEN MARKOV MODEL |
Nan Ding; Tsinghua University |
Zhijian Ou; Tsinghua University |
MLSP-P3.12: BRIDGE DETECTION AND ROBUST GEODESICS ESTIMATION VIA RANDOM WALKS |
Eugene Brevdo; Princeton University |
Peter Ramadge; Princeton University |
MLSP-P3.13: DYNAMIC FACTOR GRAPHS: A NOVEL FRAMEWORK FOR MULTIPLE FEATURES DATA FUSION |
Kittipat Kampa; University of Florida |
Jose Principe; University of Florida |
Clint Slatton; University of Florida |