Fast Algorithms for Hard Graph Problems: Bidimensionality, Minors, and (Local) Treewidth MohammadTaghi Hajiaghayi CS & AI Lab M.I.T. Joint work mainly with
Dijkstra's algorithm. O(m n log n) General case. Floyd's algorithm - all pairs shortest path ... Find a cycle passing at least once through each edge. Minimize ...
Fast Algorithms for Hard Graph Problems: Bidimensionality, Minors, and (Local) Treewidth MohammadTaghi Hajiaghayi CS & AI Lab M.I.T. Joint work mainly with
Exact (exponential) algorithms for treewidth. Fedor Fomin, Bergen, Norway ... every edge and vertex is covered by some bag. For each vertex x the set of bags ...
H(T,X) chordal. Every cycle of length 3 has a chord. Bags ... Triangulations of G: chordal supergraphs. tw(G) = min ?(H) -1. over all triangulations H of G ...
Representation and Reasoning with Graphical Models Rina Dechter Information and Computer Science, UC-Irvine, and Radcliffe Institue of Advanced Study, Cambridge
Representation and Reasoning with Graphical Models Rina Dechter Information and Computer Science, UC-Irvine, and Radcliffe Institue of Advanced Study, Cambridge
Tree decomposition Algorithm: ... [Amir 2002] Constant approximation in polytime is an important open question Local search for CSPs Hill-climbing, ...
Ab initio folding. Homology modeling. Protein threading. Stage 2: Loop Modeling ... ab. ac. clk. c. f. fgh. ij. remove dem. Side-Chain Packing Algorithm ...
... we efficiently computed all marginals using dynamic programming An HMM is a linear chain, ... often fast and good approximation Junction Trees And Belief ...
Each node specifies a distribution over its values given its ... 'Marginal Maximum A Posteriori (MAP)' max-sum-product. SP2-23. Causal vs diagnostic reasoning ...
Backtracking Procedures for Hypertree, ... Isomorphic subgraphs. a. b. c. d. e. f. g. h. i. j. a. b. d. f. g. h. i. a. b. d. g. h. i. j. Choice 2. Choice 1 ...
New algorithms for learning and inference in PGMs. to make ... Results typical convergence time. good results. early on in practice. 16. Test log-likelihood ...
Joint work with Talya Meltzer, Amir Globerson, Tommi Jaakkola, and Yair Weiss ... The marginal polytope constrains the to be marginals of some distribution: ...
Lucas Bordeaux, Youssef Hamadi. IT University of Copenhagen. Denmark ... Applications: configuration, verification, fault-trees, Bayesian networks, model ...
The Computational Complexity of Ideal Semantics I Abstract Argumentation Frameworks Paul E. Dunne Dept. Of Computer Science Univ. Of Liverpool ped@csc.liv.ac.uk
Scheduling. High multiplicity. Research motivation and applications ... Results (Ch.4): Periodic Maintenance. Algorithm from Chapter 4 solves the problem to optimality ...
(LaBRI, University of Bordeaux) Dahlia Malkhi (Hebrew Univ. of Jerusalem, Microsoft Research) ... A routing scheme allows any source node to route messages to ...
Constraint Satisfaction Problems Tuomas Sandholm Carnegie Mellon University Computer Science Department [Read Chapter 6 of Russell & Norvig] Tree-structured CSPs ...
An algorithm to compute the branchwidth of a graph on n vertices in time (2 3) ... and simple graph with |V|=n, |E|=m and let T be a ternary tree with m leaves ...
Learning Tree Conditional Random Fields Joseph K. Bradley Carlos Guestrin TO DO: SAY FRACTION EDGES RECOVERED NOT PERCENT ! Global CMI OK; local CMI bad.
Junction Trees And Belief Propagation Junction Trees: Motivation What if we want to compute all marginals, not just one? ... Remove arrows (if Bayes net) ...
Applicable to any factor graph of bounded factor size and ... Samples from PBN with unknown structure. Factor graph. Factor graph distribution P with D(PBN||P) ...
Compact Propositional Encoding of. First Order Theories. Eyal Amir ... Hi (p) : pigeon p is not in a hole in the subtree rooted at i. O(n logn) props ...
This is the a posteriori belief in X, given evidence e ... A posteriori belief. This query is useful in many cases: ... Queries: A posteriori joint ...
Ribose. YPVDLKLVVKQ binding protein. Modify sequence TNT. to change structure binding ... Side chain angles are defined moving outward from the backbone, starting ...
Hybrid Monte Carlo (use gradient information) Swendsen-Wang (large moves for Ising model) ... Combine best of both worlds (hybrid) Use smart deterministic proposals ...
For the local evidence, we can use a discriminative classifier (trained iid) ... Uses inference as subroutine (can be slow no worse than discriminative learning) ...
Inductive Definability ... Kleene and Spector. Study of inductively definable relations on N = (N, ... Sample Result: The inductive definitions of the stage ...
Rule that modifies solution to different solution. While there is a Rule(sol, sol') with ... k-opt: generalizes 3-opt. Netwerk Algorithms: TSP. 9. Lin-Kernighan ...
Mumbai. Goregaon West. 52. 1. P. City. Street. House-No. ID [Gupta&Sarawagi'2006] ...52 A Goregaon West Mumbai ... Here probabilities are meaningful. 20% of such ...
CPS 173 Auctions & Combinatorial Auctions Vincent Conitzer conitzer@cs.duke.edu A few different 1-item auction mechanisms English auction: Each bid must be higher ...
Mohammad T. Hajiaghayi University of Maryland * * * * * Outline Buy-at-bulk Network Design Prize-collecting Network Design Bidimensionality Theory Steiner Trees ...
On random graphs, no polynomial time algorithm is known to find max-IS. ... Can also certify maximality, and handle semirandom graphs [Feige, Krauthgamer 2000] ...
V. Chatalbashev, M. Collins, C. Guestrin, M. Jordan, D. Klein, ... orthography. association. What. is. the. anticipated. cost. of. collecting. fees. under. the ...
Cyril Gavoille. Bruno Courcelle. Mamadou Kant (LaBRI, Bordeaux U) Andy Twigg ... A routing scheme allows any source node to route messages to any destination ...
Theory of Networks Course Announcement Dmitri Krioukov dima@caida.org June 1st, 2005, syslunch Purpose and motivation Purpose of the presentation: introduce the ...
Rock. Paper. Rock. Matching Pennies Rochambeau (Rock-Paper-Scissors) ... of perfect rationality; can we have an alternative, 'constructive' game theory? ...
Larger super-buckets (cliques) = more time but less space. Complexity: Time: exponential in clique (super-bucket) size. Space: exponential in separator size ...
David Allen and Adnan Darwiche. Key Results. Factoring belief networks for exact inference: ... in probabilistic inference. David Allen and Adnan Darwiche ...