← Authors

Frederic Koehler

25 papers · 2016–2025 · 4 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (42) 🧭 Keyword Pioneer 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (9) πŸ† Keyword Champion (5) πŸ’Ž Century Club (25) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (10) πŸ—ƒοΈ Keyword Collector (85)

Conferences

NIPS (11) COLT (6) ICLR (4) ICML (4)

Top co-authors

Andrej Risteski (5) Raghu Meka (4) Elchanan Mossel (4) Ankur Moitra (4) Jonathan Kelner (4) Vishesh Jain (3) Lijia Zhou (3) Dhruv Rohatgi (3) Nati Srebro (2) Danica J. Sutherland (2)

Keywords

ising model (5) sparse linear regression (4) markov random field (3) graphical model (3) belief propagation (3) variational inference (2) interpolation learning (2) markov chain monte carlo (2) phase transition (2) latent variable model (2) gaussian graphical model (2) uniform convergence (2) generalization bound (2) high-dimensional statistics (2) generalized linear model (2) theoretical analysis (1) sample complexity (1) mean field approximation (1) stochastic gradient descent (1) dimensionality reduction (1)

Papers

Efficiently learning and sampling multimodal distributions with data-based initialization COLT 2025
Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting ICML 2024
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization ICLR 2024
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps COLT 2024
Feature Adaptation for Sparse Linear Regression NIPS 2023
Uniform Convergence with Square-Root Lipschitz Loss NIPS 2023
Statistical Efficiency of Score Matching: The View from Isoperimetry ICLR 2023
Reconstruction on Trees and Low-Degree Polynomials NIPS 2022
Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs NIPS 2022
Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods COLT 2022
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias ICLR 2022
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models NIPS 2022
Representational aspects of depth and conditioning in normalizing flows ICML 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting NIPS 2021
Multidimensional Scaling: Approximation and Complexity ICML 2021
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds NIPS 2020
Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability NIPS 2020
From Boltzmann Machines to Neural Networks and Back Again NIPS 2020
The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure ICLR 2019
Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation COLT 2019
Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay NIPS 2019
The Vertex Sample Complexity of Free Energy is Polynomial COLT 2018
The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity COLT 2018
Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications NIPS 2017
Provable Algorithms for Inference in Topic Models ICML 2016