UAI 2004 - PDF Preprint Papers

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UAI
2004

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Factored Latent Analysis for far-field Tracking Data

14 years 24 days ago

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This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...

Chris Stauffer

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Id	Views	Title	Status

1	228	Factored Latent Analysis for far-field Tracking Data	claim
2	207	Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms	claim
3	195	Solving Factored MDPs with Continuous and Discrete Variables	claim
4	189	A Bayesian Approach toward Active Learning for Collaborative Filtering	claim
5	169	A Complete Anytime Algorithm for Treewidth	claim
6	153	A Logic Programming Framework for Possibilistic Argumentation with Vague Knowledge	claim
7	149	Algebraic Statistics in Model Selection	claim
8	148	Bidding under Uncertainty: Theory and Experiments	claim
9	148	On the Choice of Regions for Generalized Belief Propagation	claim
10	146	Bayesian Biosurveillance of Disease Outbreaks	claim
11	143	The Minimum Information Principle for Discriminative Learning	claim
12	141	Recovering Articulated Object Models from 3D Range Data	claim
13	141	Reputation Systems: An Axiomatic Approach	claim
14	137	Dynamical Systems Trees	claim
15	135	Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences	claim
16	134	Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters	claim
17	134	Convolutional Factor Graphs as Probabilistic Models	claim
18	133	Similarity-Driven Cluster Merging Method for Unsupervised Fuzzy Clustering	claim
19	131	Dynamic Programming for Structured Continuous Markov Decision Problems	claim
20	127	Active Model Selection	claim
21	122	Computing Best-Response Strategies in Infinite Games of Incomplete Information	claim
22	122	MOB-ESP and other Improvements in Probability Estimation	claim
23	121	Discretized Approximations for POMDP with Average Cost	claim
24	117	On Finding Minimal w-cutset	claim
25	114	On-line Prediction with Kernels and the Complexity Approximation Principle	claim
26	114	Using Arguments for Making Decisions: A Possibilistic Logic Approach	claim
27	114	Applying Discrete PCA in Data Analysis	claim
28	113	Evidence-invariant Sensitivity Bounds	claim
29	112	Annealed MAP	claim
30	110	Exponential Families for Conditional Random Fields	claim
31	110	Maximum Entropy for Collaborative Filtering	claim
32	110	Regret Minimizing Equilibria and Mechanisms for Games with Strict Type Uncertainty	claim
33	109	Predictive State Representations: A New Theory for Modeling Dynamical Systems	claim
34	108	A New Characterization of Probabilities in Bayesian Networks	claim
35	108	Heuristic Search Value Iteration for POMDPs	claim
36	106	Case-Factor Diagrams for Structured Probabilistic Modeling	claim
37	106	Variational Chernoff Bounds for Graphical Models	claim
38	105	Compact Value-Function Representations for Qualitative Preferences	claim
39	102	Iterative Conditional Fitting for Gaussian Ancestral Graph Models	claim
40	101	Region-Based Incremental Pruning for POMDPs	claim
41	100	Sensitivity Analysis in Bayesian Networks: From Single to Multiple Parameters	claim
42	99	PAC-learning Bounded Tree-width Graphical Models	claim
43	99	Robust Probabilistic Inference in Distributed Systems	claim
44	98	From Fields to Trees	claim
45	98	Graph Partition Strategies for Generalized Mean Field Inference	claim
46	97	Probabilistic Index Maps for Modeling Natural Signals	claim
47	96	Monotonicity in Bayesian Networks	claim
48	95	A Generative Bayesian Model for Aggregating Experts' Probabilities	claim
49	95	Computing Nash Equilibria of Action-Graph Games	claim
50	95	An Empirical Evaluation of Possible Variations of Lazy Propagation	claim
51	95	Robustness of Causal Claims	claim
52	94	A Hierarchical Graphical Model for Record Linkage	claim
53	93	The Author-Topic Model for Authors and Documents	claim
54	92	Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials	claim
55	92	Pre-Selection of Independent Binary Features: An Application to Diagnosing Scrapie in	claim
56	89	Conditional Chow-Liu Tree Structures for Modeling Discrete-Valued Vector Time Series	claim
57	88	Mixtures of Deterministic-Probabilistic Networks and their AND/OR Search Space	claim
58	88	Identifying Conditional Causal Effects	claim
59	87	An Extended Cencov-Campbell Characterization of Conditional Information Geometry	claim
60	87	Sequential Information Elicitation in Multi-Agent Systems	claim
61	85	"Ideal Parent" Structure Learning for Continuous Variable Networks	claim
62	85	On Modeling Profiles Instead of Values	claim
63	84	Exploiting First-Order Regression in Inductive Policy Selection	claim

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