Search Results - "Bresler, Guy"
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1
Feasibility of Interference Alignment for the MIMO Interference Channel
Published in IEEE transactions on information theory (01-09-2014)“…We study vector space interference alignment for the multiple-input multiple-output interference channel with no time or frequency diversity, and no symbol…”
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LEARNING A TREE-STRUCTURED ISING MODEL IN ORDER TO MAKE PREDICTIONS
Published in The Annals of statistics (01-04-2020)“…We study the problem of learning a tree Ising model from samples such that subsequent predictions made using the model are accurate. The prediction task…”
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3
Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering
Published in IEEE transactions on information theory (01-06-2021)“…We consider an online model for recommendation systems, with each user being recommended an item at each time-step and providing 'like' or 'dislike' feedback…”
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4
STEIN’S METHOD FOR STATIONARY DISTRIBUTIONS OF MARKOV CHAINS AND APPLICATION TO ISING MODELS
Published in The Annals of applied probability (01-10-2019)“…We develop a new technique, based on Stein’s method, for comparing two stationary distributions of irreducible Markov chains whose update rules are close in a…”
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5
The Algorithmic Phase Transition of Random k-SAT for Low Degree Polynomials
Published in 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS) (01-02-2022)“…Let \Phi be a uniformly random k -SAT formula with n variables and m clauses. We study the algorithmic task of finding a satisfying assignment of \Phi . It is…”
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Conference Proceeding -
6
The two-user Gaussian interference channel: a deterministic view
Published in European transactions on telecommunications (01-06-2008)“…This paper explores the two‐user Gaussian interference channel through the lens of a natural deterministic channel model. The main result is that the…”
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7
Metastable mixing of Markov chains: Efficiently sampling low temperature exponential random graphs
Published in The Annals of applied probability (01-02-2024)“…In this paper, we consider the problem of sampling from the low-temperature exponential random graph model (ERGM). The usual approach is via Markov chain Monte…”
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8
Learning Graphical Models From the Glauber Dynamics
Published in IEEE transactions on information theory (01-06-2018)“…In this paper, we consider the problem of learning undirected graphical models from data generated according to the Glauber dynamics (also known as the Gibbs…”
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9
Information Storage in the Stochastic Ising Model
Published in IEEE transactions on information theory (01-03-2021)“…Most information storage devices write data by modifying the local state of matter, in the hope that sub-atomic local interactions stabilize the state for…”
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10
Optimal assembly for high throughput shotgun sequencing
Published in BMC bioinformatics (2013)“…We present a framework for the design of optimal assembly algorithms for shotgun sequencing under the criterion of complete reconstruction. We derive a lower…”
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11
Phase transitions for detecting latent geometry in random graphs
Published in Probability theory and related fields (01-12-2020)“…Random graphs with latent geometric structure are popular models of social and biological networks, with applications ranging from network user profiling to…”
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12
Threshold for detecting high dimensional geometry in anisotropic random geometric graphs
Published in Random structures & algorithms (01-01-2024)“…In the anisotropic random geometric graph model, vertices correspond to points drawn from a high‐dimensional Gaussian distribution and two vertices are…”
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13
MIXING TIME OF EXPONENTIAL RANDOM GRAPHS
Published in The Annals of applied probability (01-12-2011)“…A variety of random graph models has been developed in recent years to study a range of problems on networks, driven by the wide availability of data from many…”
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14
Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs: The Case of Extra Triangles
Published in 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS) (06-11-2023)“…We aim to understand the extent to which the noise distribution in a planted signal-plus-noise problem impacts its computational complexity. To that end, we…”
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Conference Proceeding -
15
Information Theory of DNA Shotgun Sequencing
Published in IEEE transactions on information theory (01-10-2013)“…DNA sequencing is the basic workhorse of modern day biology and medicine. Shotgun sequencing is the dominant technique used: many randomly located short…”
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16
Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models
Published in 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS) (01-02-2022)“…We consider the problem of learning a tree-structured Ising model from data, such that subsequent predictions computed using the model are accurate…”
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Conference Proceeding -
17
The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels
Published in IEEE transactions on information theory (01-09-2010)“…Recently, Etkin, Tse, and Wang found the capacity region of the two-user Gaussian interference channel to within 1 bit/s/Hz. A natural goal is to apply this…”
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18
Feasibility of interference alignment for the MIMO interference channel: The symmetric square case
Published in 2011 IEEE Information Theory Workshop (01-10-2011)“…Determining the feasibility conditions for vector space interference alignment in the K-user MIMO interference channel with constant channel coefficients has…”
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Conference Proceeding -
19
The Average-Case Complexity of Counting Cliques in Erdős-Rényi Hypergraphs
Published in 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS) (01-11-2019)“…The complexity of clique problems on Erdos-Renyi random graphs has become a central topic in average-case complexity. Algorithmic phase transitions in these…”
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Conference Proceeding -
20
Sandwiching Random Geometric Graphs and Erdos-Renyi with Applications: Sharp Thresholds, Robust Testing, and Enumeration
Published 01-08-2024“…The distribution $\mathsf{RGG}(n,\mathbb{S}^{d-1},p)$ is formed by sampling independent vectors $\{V_i\}_{i = 1}^n$ uniformly on $\mathbb{S}^{d-1}$ and placing…”
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