Andrea Montanari
Professor of Electrical Engineering and of Statistics
Bio
I am interested in developing efficient algorithms to make sense of large amounts of noisy data, extract information from observations, estimate signals from measurements. This effort spans several disciplines including statistics, computer science, information theory, machine learning.
I am also working on applications of these techniques to healthcare data analytics.
Professional Education
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PhD, Scuola Normale Superiore, Pisa, Italy (2001)
2015-16 Courses
- Literature of Statistics
STATS 319 (Spr) - Modern Coding Theory
EE 388 (Win) - Probabilistic Systems Analysis
EE 178 (Spr) - Theory of Probability
MATH 230A, STATS 310A (Aut) -
Independent Studies (19)
- Advanced Reading and Research
CS 499 (Aut, Win) - Independent Study
STATS 199 (Aut, Win, Spr, Sum) - Independent Study
STATS 299 (Aut, Win, Spr, Sum) - Industrial Research for Statisticians
STATS 298 (Aut, Win, Spr, Sum) - Industrial Research for Statisticians
STATS 398 (Aut, Win, Spr, Sum) - Master's Thesis and Thesis Research
EE 300 (Aut, Win, Spr) - Part-Time CPT
CS 390S (Aut) - Part-Time CPT
CS 390T (Win) - Part-Time Curricular Practical Training
CS 390Q (Spr) - Part-time Curricular Practical Training
CS 390P (Win, Spr) - Ph.D. Research
CME 400 (Aut, Win, Spr, Sum) - Research
STATS 399 (Aut, Win, Spr, Sum) - Senior Project
CS 191 (Aut) - Special Studies and Reports in Electrical Engineering
EE 191 (Aut, Spr) - Special Studies and Reports in Electrical Engineering
EE 391 (Aut, Win, Spr, Sum) - Special Studies and Reports in Electrical Engineering (WIM)
EE 191W (Aut, Win, Spr) - Special Studies or Projects in Electrical Engineering
EE 190 (Aut, Spr) - Special Studies or Projects in Electrical Engineering
EE 390 (Aut, Win, Spr, Sum) - Writing Intensive Senior Project (WIM)
CS 191W (Aut)
- Advanced Reading and Research
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Prior Year Courses
2014-15 Courses
- Inference, Estimation, and Information Processing
EE 378B (Spr) - Stochastic Processes on Graphs
STATS 316 (Aut)
2013-14 Courses
- Probabilistic Systems Analysis
EE 178, EE 278A (Aut) - Theory of Probability
MATH 230B, STATS 310B (Win)
2012-13 Courses
- Inference, Estimation, and Information Processing
EE 378B (Spr) - Probabilistic Systems Analysis
EE 178, EE 278A (Spr) - Theory of Probability
MATH 230A, STATS 310A (Aut)
- Inference, Estimation, and Information Processing
All Publications
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Localization from Incomplete Noisy Distance Measurements
FOUNDATIONS OF COMPUTATIONAL MATHEMATICS
2013; 13 (3): 297-345
View details for DOI 10.1007/s10208-012-9129-5
View details for Web of Science ID 000318174900001
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The phase transition of matrix recovery from Gaussian measurements matches the minimax MSE of matrix denoising
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2013; 110 (21): 8405-8410
Abstract
Let X(0) be an unknown M by N matrix. In matrix recovery, one takes n < MN linear measurements y(1),…,y(n) of X(0), where y(i) = Tr(A(T)iX(0)) and each A(i) is an M by N matrix. A popular approach for matrix recovery is nuclear norm minimization (NNM): solving the convex optimization problem min ||X||*subject to y(i) =Tr(A(T)(i)X) for all 1 ≤ i ≤ n, where || · ||* denotes the nuclear norm, namely, the sum of singular values. Empirical work reveals a phase transition curve, stated in terms of the undersampling fraction δ(n,M,N) = n/(MN), rank fraction ρ=rank(X0)/min {M,N}, and aspect ratio β=M/N. Specifically when the measurement matrices Ai have independent standard Gaussian random entries, a curve δ*(ρ) = δ*(ρ;β) exists such that, if δ > δ*(ρ), NNM typically succeeds for large M,N, whereas if δ < δ*(ρ), it typically fails. An apparently quite different problem is matrix denoising in Gaussian noise, in which an unknown M by N matrix X(0) is to be estimated based on direct noisy measurements Y =X(0) + Z, where the matrix Z has independent and identically distributed Gaussian entries. A popular matrix denoising scheme solves the unconstrained optimization problem min|| Y-X||(2)(F)/2+λ||X||*. When optimally tuned, this scheme achieves the asymptotic minimax mean-squared error M(ρ;β) = lim(M,N → ∞)inf(λ)sup(rank(X) ≤ ρ · M)MSE(X,X(λ)), where M/N → . We report extensive experiments showing that the phase transition δ*(ρ) in the first problem, matrix recovery from Gaussian measurements, coincides with the minimax risk curve M(ρ)=M(ρ;β) in the second problem, matrix denoising in Gaussian noise: δ*(ρ)=M(ρ), for any rank fraction 0 < ρ < 1 (at each common aspect ratio β). Our experiments considered matrices belonging to two constraint classes: real M by N matrices, of various ranks and aspect ratios, and real symmetric positive-semidefinite N by N matrices, of various ranks.
View details for DOI 10.1073/pnas.1306110110
View details for Web of Science ID 000320328700032
View details for PubMedID 23650360
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Iterative Coding for Network Coding
IEEE TRANSACTIONS ON INFORMATION THEORY
2013; 59 (3): 1563-1572
View details for DOI 10.1109/TIT.2012.2236912
View details for Web of Science ID 000315120400021
- Factor models on locally tree-like graphs Annals of Probability 2013
- Finding Hidden Cliques of Size in Nearly Linear Time 2013
- Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory 2013
- Confidence Intervals and Hypothesis Testing for High-Dimensional Regression 2013
- High Dimensional Robust M-Estimation: Asymptotic Variance via Approximate Message Passing 2013
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Lossy Compression of Discrete Sources via the Viterbi Algorithm
IEEE TRANSACTIONS ON INFORMATION THEORY
2012; 58 (4): 2475-2489
View details for DOI 10.1109/TIT.2011.2178059
View details for Web of Science ID 000302079800033
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The LASSO Risk for Gaussian Matrices
IEEE TRANSACTIONS ON INFORMATION THEORY
2012; 58 (4): 1997-2017
View details for DOI 10.1109/TIT.2011.2174612
View details for Web of Science ID 000302079800001
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The weak limit of Ising models on locally tree-like graphs
PROBABILITY THEORY AND RELATED FIELDS
2012; 152 (1-2): 31-51
View details for DOI 10.1007/s00440-010-0315-6
View details for Web of Science ID 000299131700002
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Subsampling at Information Theoretically Optimal Rates
2012 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS (ISIT)
2012
View details for Web of Science ID 000312544302106
- Universality in Polytope Phase Transitions and Message Passing Algorithms 2012
- The noise sensitivity phase transition in compressed sensing IEEE Transactions on Information Theory 2012
- Graphical Models Concepts in Compressed Sensing in Compressed Sensing Cambridge university PRess. 2012: 1
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Universality in Polytope Phase Transitions and Iterative Algorithms
2012 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS (ISIT)
2012
View details for Web of Science ID 000312544301149
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Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing
2012 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS (ISIT)
2012
View details for Web of Science ID 000312544301066
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ACCELERATED TIME-OF-FLIGHT MASS SPECTROMETRY
2012 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP)
2012: 432-435
View details for Web of Science ID 000309943200109
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The Noise-Sensitivity Phase Transition in Compressed Sensing
IEEE TRANSACTIONS ON INFORMATION THEORY
2011; 57 (10): 6920-6941
View details for DOI 10.1109/TIT.2011.2165823
View details for Web of Science ID 000295739000043
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MAJORITY DYNAMICS ON TREES AND THE DYNAMIC CAVITY METHOD
ANNALS OF APPLIED PROBABILITY
2011; 21 (5): 1694-1748
View details for DOI 10.1214/10-AAP729
View details for Web of Science ID 000297027800003
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Applications of the Lindeberg Principle in Communications and Statistical Learning
IEEE TRANSACTIONS ON INFORMATION THEORY
2011; 57 (4): 2440-2450
View details for DOI 10.1109/TIT.2011.2112231
View details for Web of Science ID 000288459100044
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The Dynamics of Message Passing on Dense Graphs, with Applications to Compressed Sensing
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2011: 764-785
View details for DOI 10.1109/TIT.2010.2094817
View details for Web of Science ID 000286514200014
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Subexponential convergence for information aggregation on regular trees
2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC)
2011: 5317-5322
View details for Web of Science ID 000303506205152
- Gossip PCA 2011
- Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising 2011
- Factor models on locally tree-like graphs 2011
- Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing 2011
- Distributed Storage for Intermittent Energy Sources: Control Design and Performance Limits 2011
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Fast Convergence of Natural Bargaining Dynamics in Exchange Networks
PROCEEDINGS OF THE TWENTY-SECOND ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS
2011: 1518-1537
View details for Web of Science ID 000296182400118
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Localization from Incomplete Noisy Distance Measurements
2011 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS (ISIT)
2011: 1584-1588
View details for Web of Science ID 000297465101155
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Compressed Sensing over l(p)-balls: Minimax Mean Square Error
IEEE. 2011: 129-133
View details for Web of Science ID 000297465100027
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RECONSTRUCTION AND CLUSTERING IN RANDOM CONSTRAINT SATISFACTION PROBLEMS
SIAM JOURNAL ON DISCRETE MATHEMATICS
2011; 25 (2): 771-808
View details for DOI 10.1137/090755862
View details for Web of Science ID 000292302000024
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Information Theoretic Limits on Learning Stochastic Differential Equations
2011 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS (ISIT)
2011: 855-859
View details for Web of Science ID 000297465101007
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The spread of innovations in social networks
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2010; 107 (47): 20196-20201
Abstract
Which network structures favor the rapid spread of new ideas, behaviors, or technologies? This question has been studied extensively using epidemic models. Here we consider a complementary point of view and consider scenarios where the individuals' behavior is the result of a strategic choice among competing alternatives. In particular, we study models that are based on the dynamics of coordination games. Classical results in game theory studying this model provide a simple condition for a new action or innovation to become widespread in the network. The present paper characterizes the rate of convergence as a function of the structure of the interaction network. The resulting predictions differ strongly from the ones provided by epidemic models. In particular, it appears that innovation spreads much more slowly on well-connected network structures dominated by long-range links than in low-dimensional ones dominated, for example, by geographic proximity.
View details for DOI 10.1073/pnas.1004098107
View details for Web of Science ID 000284529000013
View details for PubMedID 21076030
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Matrix Completion from Noisy Entries
JOURNAL OF MACHINE LEARNING RESEARCH
2010; 11: 2057-2078
View details for Web of Science ID 000282523000005
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Matrix Completion From a Few Entries
IEEE TRANSACTIONS ON INFORMATION THEORY
2010; 56 (6): 2980-2998
View details for DOI 10.1109/TIT.2010.2046205
View details for Web of Science ID 000277880200039
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ISING MODELS ON LOCALLY TREE-LIKE GRAPHS
ANNALS OF APPLIED PROBABILITY
2010; 20 (2): 565-592
View details for DOI 10.1214/09-AAP627
View details for Web of Science ID 000283529500007
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Regularization for Matrix Completion
2010 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY
2010: 1503-1507
View details for Web of Science ID 000287512700303
- Learning Networks of Stochastic Differential Equations 2010
- Tight Thresholds for Cuckoo Hashing via XORSAT 2010
- The LASSO risk: asymptotic results and real world examples 2010
- Gibbs Measures and Phase Transitions on Sparse Random Graphs Brazilian Journal of Probability and Statistics 2008 Brazilian School of Probability. 2010: 1
- Ising models on locally tree-like graphs Annals of Applied Probability 2010
- Fast Convergence of Natural Bargaining Dynamics in Exchange Networks 2010
- Majority dynamics on trees and the dynamic cavity method Annals of Applied Probability 2010
- The Spread of Innovations in Social Networks 2010
- Graphical Models Concepts in Compressed Sensing 2010
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On the deletion channel with small deletion probability
2010 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY
2010: 1002-1006
View details for Web of Science ID 000287512700201
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The dynamics of message passing on dense graphs, with applications to compressed sensing
2010 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY
2010: 1528-1532
View details for Web of Science ID 000287512700308
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Tight Thresholds for Cuckoo Hashing via XORSAT
AUTOMATA, LANGUAGES AND PROGRAMMING, PT I
2010; 6198: 213-225
View details for Web of Science ID 000286345400019
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An Empirical Scaling Law for Polar Codes
2010 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY
2010: 884-888
View details for Web of Science ID 000287512700177
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Message-passing algorithms for compressed sensing
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2009; 106 (45): 18914-18919
Abstract
Compressed sensing aims to undersample certain high-dimensional signals yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to be recovered is sufficiently sparse in a known basis. Currently, the best known sparsity-undersampling tradeoff is achieved when reconstructing by convex optimization, which is expensive in important large-scale applications. Fast iterative thresholding algorithms have been intensively studied as alternatives to convex optimization for large-scale problems. Unfortunately known fast algorithms offer substantially worse sparsity-undersampling tradeoffs than convex optimization. We introduce a simple costless modification to iterative thresholding making the sparsity-undersampling tradeoff of the new algorithms equivalent to that of the corresponding convex optimization procedures. The new iterative-thresholding algorithms are inspired by belief propagation in graphical models. Our empirical measurements of the sparsity-undersampling tradeoff for the new algorithms agree with theoretical calculations. We show that a state evolution formalism correctly derives the true sparsity-undersampling tradeoff. There is a surprising agreement between earlier calculations based on random convex polytopes and this apparently very different theoretical formalism.
View details for DOI 10.1073/pnas.0909892106
View details for Web of Science ID 000271637500010
View details for PubMedID 19858495
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The Generalized Area Theorem and Some of its Consequences
IEEE TRANSACTIONS ON INFORMATION THEORY
2009; 55 (11): 4793-4821
View details for DOI 10.1109/TIT.2009.2030457
View details for Web of Science ID 000271019700001
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Finite-Length Scaling for Iteratively Decoded LDPC Ensembles
IEEE TRANSACTIONS ON INFORMATION THEORY
2009; 55 (2): 473-498
View details for DOI 10.1109/TIT.2008.2009580
View details for Web of Science ID 000263375500001
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Low-rank Matrix Completion with Noisy Observations: a Quantitative Comparison
2009 47TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING, VOLS 1 AND 2
2009: 1216-1222
View details for Web of Science ID 000279627100166
- Generating Random Graphs with Large Girth 2009
- Matrix Completion from a Few Entries 2009
- Matrix Completion from Noisy Entries 2009
- Which graphical models are difficult to learn? 2009
- Information, Physics, and Computation Oxford University Press. 2009
- An Implementable Scheme for Universal Lossy Compression of Discrete Markov Sources 2009
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Matrix Completion from a Few Entries
2009 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, VOLS 1- 4
2009: 324-328
View details for Web of Science ID 000280141400067
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Convergence to Equilibrium in Local Interaction Games
2009 50TH ANNUAL IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE: FOCS 2009, PROCEEDINGS
2009: 303-312
View details for DOI 10.1109/FOCS.2009.64
View details for Web of Science ID 000278330300030
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Generating random Tanner-graphs with large girth
2009 IEEE INFORMATION THEORY WORKSHOP (ITW 2009)
2009: 154-157
View details for Web of Science ID 000305809200032
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An Iterative Scheme for Near Optimal and Universal Lossy Compression
ITW: 2009 IEEE INFORMATION THEORY WORKSHOP ON NETWORKING AND INFORMATION THEORY
2009: 231-235
View details for Web of Science ID 000273966100049
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Generating Random Graphs with Large Girth
PROCEEDINGS OF THE TWENTIETH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS
2009: 566-575
View details for Web of Science ID 000281447000063
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Maxwell Construction: The Hidden Bridge Between Iterative and Maximum a Posteriori Decoding
IEEE TRANSACTIONS ON INFORMATION THEORY
2008; 54 (12): 5277-5307
View details for DOI 10.1109/TIT.2008.2006466
View details for Web of Science ID 000261648100001
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Estimating random variables from random sparse observations
EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS
2008; 19 (4): 385-403
View details for DOI 10.1002/ett.1289
View details for Web of Science ID 000257012200005
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Clusters of solutions and replica symmetry breaking in random k-satisfi ability
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
2008
View details for DOI 10.1088/1742-5468/2008/04/P04004
View details for Web of Science ID 000255662000008
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Counter Braids
2008 IEEE INFORMATION THEORY WORKSHOP
2008: 220-221
View details for Web of Science ID 000259299000048
- Finite Size Scaling for the Core of Large Random Hypergraphs Annals of Applied Probability 2008
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Counter Braids: A Novel Counter Architecture for Per-Flow Measurement
SIGMETRICS'08: PROCEEDINGS OF THE 2008 INTERNATIONAL CONFERENCE ON MEASUREMENT & MODELING OF COMPUTER SYSTEMS
2008; 36 (1): 121-132
View details for Web of Science ID 000266429500011
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Counter Braids: Asymptotic Optimality of the Message Passing Decoding Algorithm
2008 46TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING, VOLS 1-3
2008: 209-216
View details for Web of Science ID 000268229600032
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Learning Low Rank Matrices from O(n) Entries
2008 46TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING, VOLS 1-3
2008: 1365-1372
View details for Web of Science ID 000268229600194
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Computing the threshold shift for general channels
2008 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-6
2008: 1448-1452
View details for Web of Science ID 000260364401010
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An Implementable Scheme for Universal Lossy Compression of Discrete Markov Sources
DCC 2009: 2009 DATA COMPRESSION CONFERENCE, PROCEEDINGS
2008: 292-301
View details for DOI 10.1109/DCC.2009.72
View details for Web of Science ID 000268029900030
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The Slope Scaling Parameter for General Channels, Decoders, and Ensembles
2008 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-6
2008: 1443-1447
View details for Web of Science ID 000260364401009
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Smooth compression, Gallager bound and Nonlinear sparse-graph codes
2008 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-6
2008: 2474-2478
View details for Web of Science ID 000260364401219
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A simple one dimensional glassy Kac model
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
2007
View details for DOI 10.1088/1742-5468/2007/08/P08004
View details for Web of Science ID 000249277600007
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How to find good finite-length codes: from art towards science
WILEY-BLACKWELL. 2007: 491-508
View details for DOI 10.1002/ett.1182
View details for Web of Science ID 000248443400007
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Gibbs states and the set of solutions of random constraint satisfaction problems
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2007; 104 (25): 10318-10323
Abstract
An instance of a random constraint satisfaction problem defines a random subset (the set of solutions) of a large product space chiN (the set of assignments). We consider two prototypical problem ensembles (random k-satisfiability and q-coloring of random regular graphs) and study the uniform measure with support on S. As the number of constraints per variable increases, this measure first decomposes into an exponential number of pure states ("clusters") and subsequently condensates over the largest such states. Above the condensation point, the mass carried by the n largest states follows a Poisson-Dirichlet process. For typical large instances, the two transitions are sharp. We determine their precise location. Further, we provide a formal definition of each phase transition in terms of different notions of correlation between distinct variables in the problem. The degree of correlation naturally affects the performances of many search/sampling algorithms. Empirical evidence suggests that local Monte Carlo Markov chain strategies are effective up to the clustering phase transition and belief propagation up to the condensation point. Finally, refined message passing techniques (such as survey propagation) may also beat this threshold.
View details for DOI 10.1073/pnas.0703685104
View details for Web of Science ID 000247500000006
View details for PubMedID 17567754
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Reconstruction for models on random graphs
48TH ANNUAL IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE, PROCEEDINGS
2007: 194-204
View details for DOI 10.1109/FOCS.2007.58
View details for Web of Science ID 000252161900018
- Detailed Network Measurements Using Sparse Graph Counters: The Theory 2007
- TP Decoding 2007
- Counting Good Truth Assignmants for Random Satisfiability Formulae 2007
- Solving Constraint Satisfaction Problems through Belief Propagation-guided Decimation 2007
- Modern Coding Theory: The Statistical Mechanics and Computer Science Point of View Les Houches Summer School on Mathematical Statistical Physics Elsevier. 2007: 1
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A generalization of the finite-length scaling approach beyond the BEC
2007 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-7
2007: 1011-1015
View details for Web of Science ID 000257010201034
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Asymptotic rate versus design rate
2007 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-7
2007: 1541-1545
View details for Web of Science ID 000257010201140
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Precision electroweak measurements on the Z resonance
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
2006; 427 (5-6): 257-454
View details for DOI 10.1016/j.physrep.2005.12.006
View details for Web of Science ID 000236815000001
- How to Find Good Finite-Length Codes: From Art Towards Science European Transactions on Telecommunications 2006
- Finite-Length Scaling for Gallager A 2006
- Two Lectures on Iterative Coding and Statistical Mechanics Les Houches Summer School on Mathematical Statistical Physics Elsevier. 2006: 1
- The Asymptotic Error Floor of LDPC Ensembles Under BP Decoding 2006
- Analysis of Belief propagation for Non-Linear Problems: The Example of CDMA (or: How to Prove Tanaka's Formula) 2006
- Approximate analysis of search algorithms with “physical” methods Phase Transitions and Algorithmic Complexity Oxford. 2006: 1
- Why We Can Not Surpass Capacity: The Matching Condition 2005
- From Large Scale Rearrangements to Mode Coupling Phenomenology Physical Review Letters 2005
- How to Compute Loop Corrections to Bethe Approximation Journal of Statistical Mechanics 2005
- Tight bounds for LDPC and LDGM codes under MAP decoding IEEE Transactions on Information Theory 2005
- Belief Propagation Based Multi–User Detection 2005
- Life Above Threshold: From List Decoding to Area Theorem and MSE 2004
- Finite-Length Scaling and Finite-Length Shift for Low-Density Parity-Check Codes 2004
- Instability of one-step replica-symmetry-broken phase in satisfiability problems Journal of Physics A 2004
- Tight bounds for LDPC codes under MAP decoding 2004
- On the stochastic dynamics of disordered spin models Journal of Statistical Physics 2004
- The Phase Diagram of Random Heteropolymers Physical Review Letters 2004
- Glassy phases in Random Heteropolymers with correlated sequences Journal of Chemical Physics 2004
- On the cooling-schedule dependence of the dynamics of mean-field glasses Physical Review B 2004
- Finite-length scaling for iteratively decoded LDPC ensembles 2003
- A microscopic description of the aging dynamics: fluctuation-dissipation relations, effective temperature and heterogeneities Physical Review Letters 2003
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Alternative translation techniques for propositional and first-order modal logics
JOURNAL OF AUTOMATED REASONING
2002; 28 (4): 397-415
View details for Web of Science ID 000176183400003
- The dynamic phase transition for decoding algorithms Physical Review E 2002; 66
- Optimizing searches via rare events Physical Review Letters 2002
- Discrete non-Abelian groups and asymptotically free models 2001
- The glassy phase of Gallager codes The European Physical Journal B 2001
- Statistical mechanics and turbo codes 2001
- Finite-size scaling and metastable states of good codes 2001
- Asymptotically free models and discrete non-Abelian groups Physics Letters B 2001
- Hairpin formation and elongation of biomolecules Physical Review Letters 2001
- Spin models on Platonic solids and asymptotic freedom 2001
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A guided tour through some extensions of the event calculus
COMPUTATIONAL INTELLIGENCE
2000; 16 (2): 307-347
View details for Web of Science ID 000086463100007
- Turbo codes: the phase transition The European Physical Journal B 2000
- The statistical mechanics of turbo codes The European Physical Journal B 2000
- Operator product expansion on the lattice: a numerical test in the two-dimensional non-linear sigma-model Journal of High Energy Physics 2000
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A general modal framework for the Event Calculus and its skeptical and credulous variants
JOURNAL OF LOGIC PROGRAMMING
1999; 38 (2): 111-164
View details for Web of Science ID 000077705000001
- Testing the efficiency of different improvement programs Nuclear Physics B 1999
- Composite operators from operator product expansion: what can go wrong? 1999
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Event Calculus with explicit quantifiers
FIFTH INTERNATIONAL WORKSHOP ON TEMPORAL REPRESENTATION AND REASONING - PROCEEDINGS
1998: 81-88
View details for Web of Science ID 000074225400013
- Operator product expansion and non-perturbative renormalization 1998
- Improved actions for the two-dimensional sigma-model 1997
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COEVAL AR-40/AR-39 AGES OF 65.0 MILLION YEARS AGO FROM CHICXULUB CRATER MELT ROCK AND CRETACEOUS-TERTIARY BOUNDARY TEKTITES
SCIENCE
1992; 257 (5072): 954-958
Abstract
(40)Ar/(39)Ar dating of drill core samples of a glassy melt rock recovered from beneath a massive impact breccia contained within the 180-kilometer subsurface Chicxulub crater in Yucatán, Mexico, has yielded well-behaved incremental heating spectra with a mean plateau age of 64.98 +/- 0.05 million years ago (Ma). The glassy melt rock of andesitic composition was obtained from core 9 (1390 to 1393 meters) in the Chicxulub 1 well. The age of the melt rock is virtually indistinguishable from (40)Ar/(39)Ar ages obtained on tektite glass from Beloc, Haiti, and Arroyo el Mimbral, northeastern Mexico, of 65.01 +/- 0.08 Ma (mean plateau age for Beloc) and 65.07 +/- 0.10 Ma (mean total fusion age for both sites). The (40)Ar/(39)Ar ages, in conjunction with geochemical and petrological similarities, strengthen the recent suggestion that the Chicxulub structure is the source for the Haitian and Mexican tektites and is a viable candidate for the Cretaceous-Tertiary boundary impact site.
View details for Web of Science ID A1992JH82700032
View details for PubMedID 17789640