Alexander Ihler
22 papers · 2005–2026 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (36) π Academic Marathon Β· Ultra π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π±
Topic Pioneer
π€
Dynamic Duo
(11)
π
Renaissance Researcher
(5)
π
Conference Pioneer
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(94)
π₯
Unstoppable Β· Bronze
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Trend Setter
Top co-authors
Research topics
Machine Learning
(17)
Optimization & Theory
(11)
Artificial Intelligence
(9)
Mathematics & Optimization
(9)
Bayesian & Probabilistic Β· Machine Learning
(7)
Optimization
(7)
Core AI
(6)
Bayesian & Probabilistic Β· Artificial Intelligence
(5)
Core Methods
(5)
Deep Learning
(3)
Learning Types
(3)
Mathematics
(3)
Knowledge & Reasoning
(2)
Reasoning
(2)
Computer Science
(1)
Keywords
graphical model
(9)
marginal map
(4)
best-first search
(2)
computational protein design
(2)
boltzmann machine
(2)
importance sampling
(2)
approximate inference
(2)
message passing
(2)
monte carlo method
(2)
abstraction sampling
(2)
probabilistic inference
(2)
variational inference
(2)
anytime algorithm
(2)
mixed inference
(2)
sparse estimation
(1)
sample efficiency
(1)
parameter estimation
(1)
reinforcement learning
(1)
model compression
(1)
latent dirichlet allocation
(1)
Papers
Variance Estimation and Selecting Good Estimands for Causal Effect Queries
UAI 2026
Graph-based Complexity for Causal Effect by Empirical Plug-in
AISTATS 2025
Value-Based Abstraction Functions for Abstraction Sampling
UAI 2024
Boosting AND/OR-based computational protein design: dynamic heuristics and generalizable UFO
UAI 2023
Design Amortization for Bayesian Optimal Experimental Design
AAAI 2023
AND/OR branch-and-bound for computational protein design optimizing K*
UAI 2022
Be Like Water: Adaptive Floating Point for Machine Learning
ICML 2022
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks
ICML 2022
Scaling Up AND/OR Abstraction Sampling
IJCAI 2020
Anytime Recursive Best-First Search for Bounding Marginal MAP
AAAI 2019
A Weighted Mini-Bucket Bound for Solving Influence Diagram
UAI 2019
Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms
AAAI 2019
Accelerating Dynamic Programs via Nested Benders Decomposition with Application to Multi-Person Pose Estimation
ECCV 2018
ContextNet: Deep learning for Star Galaxy Classification
ICML 2018
Stochastic Anytime Search for Bounding Marginal MAP
IJCAI 2018
Pushing Forward Marginal MAP with Best-First Search
IJCAI 2015
Linear Approximation to ADMM for MAP inference
ACML 2013
Learning Scale Free Networks by Reweighted β_1 regularization
AISTATS 2011
Multicore Gibbs Sampling in Dense, Unstructured Graphs
AISTATS 2011
Revisiting MAP Estimation, Message Passing and Perfect Graphs
AISTATS 2011
Learning with Blocks: Composite Likelihood and Contrastive Divergence
AISTATS 2010
Particle Belief Propagation
AISTATS 2005