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Logistic-Regression with peer-group effects via inference in higher
  order Ising models

Logistic-Regression with peer-group effects via inference in higher order Ising models

International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
18 March 2020
C. Daskalakis
Nishanth Dikkala
Ioannis Panageas
ArXiv (abs)PDFHTML

Papers citing "Logistic-Regression with peer-group effects via inference in higher order Ising models"

10 / 10 papers shown
Estimating Ising Models in Total Variation Distance
Estimating Ising Models in Total Variation Distance
C. Daskalakis
Vardis Kandiros
Rui-Min Yao
231
0
0
26 Nov 2025
Learning the Inverse Temperature of Ising Models under Hard Constraints using One Sample
Learning the Inverse Temperature of Ising Models under Hard Constraints using One Sample
Rohan Chauhan
Ioannis Panageas
144
0
0
25 Sep 2025
One-Shot Learning for k-SAT
One-Shot Learning for k-SATInternational Colloquium on Automata, Languages and Programming (ICALP), 2025
Andreas Galanis
Leslie Ann Goldberg
Xusheng Zhang
358
0
0
10 Feb 2025
Nonsense associations in Markov random fields with pairwise dependence
Nonsense associations in Markov random fields with pairwise dependenceBiometrika (Biometrika), 2024
Sohom Bhattacharya
Rajarshi Mukherjee
Elizabeth Ogburn
142
1
0
05 Feb 2024
PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
Abhinav Chakraborty
Anirban Chatterjee
Abhinandan Dalal
265
0
0
29 Jan 2024
Limit Theorems and Phase Transitions in the Tensor Curie-Weiss Potts
  Model
Limit Theorems and Phase Transitions in the Tensor Curie-Weiss Potts ModelInformation and Inference A Journal of the IMA (JIII), 2023
Sanchayan Bhowal
Somabha Mukherjee
347
4
0
03 Jul 2023
Estimation in Tensor Ising Models
Estimation in Tensor Ising Models
Somabha Mukherjee
Jaesung Son
B. Bhattacharya
381
15
0
29 Aug 2020
Parameter Estimation for Undirected Graphical Models with Hard
  Constraints
Parameter Estimation for Undirected Graphical Models with Hard Constraints
B. Bhattacharya
K. Ramanan
391
4
0
22 Aug 2020
Learning of Discrete Graphical Models with Neural Networks
Learning of Discrete Graphical Models with Neural Networks
Abhijith Jayakumar
A. Lokhov
Sidhant Misra
Marc Vuffray
CML
307
10
0
21 Jun 2020
Phase Transitions of the Maximum Likelihood Estimates in the $p$-Spin
  Curie-Weiss Model
Phase Transitions of the Maximum Likelihood Estimates in the ppp-Spin Curie-Weiss Model
Somabha Mukherjee
Jaesung Son
B. Bhattacharya
586
21
0
07 May 2020
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