Alexander Ihler

Orcid: 0000-0002-4331-1015

Affiliations:
  • University of California, Irvine, Department of Computer Science


According to our database1, Alexander Ihler authored at least 113 papers between 1999 and 2024.

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Bibliography

2024
Pipe Routing with Topology Control for UAV Networks.
CoRR, 2024

2023
A Cross-Layer, Mobility, and Congestion-Aware Routing Protocol for UAV Networks.
IEEE Trans. Aerosp. Electron. Syst., August, 2023

A Deep Q-Learning based, Base-Station Connectivity-Aware, Decentralized Pheromone Mobility Model for Autonomous UAV Networks.
CoRR, 2023

Boosting AND/OR-based computational protein design: dynamic heuristics and generalizable UFO.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Deep Q-Learning Connectivity-Aware Pheromone Mobility Model for Autonomous UAV Networks.
Proceedings of the International Conference on Computing, Networking and Communications, 2023

A Connectivity-Aware Pheromone Mobility Model for Autonomous UAV Networks.
Proceedings of the 20th IEEE Consumer Communications & Networking Conference, 2023

Design Amortization for Bayesian Optimal Experimental Design.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Accurate Link Lifetime Computation in Autonomous Airborne UAV Networks.
CoRR, 2022

AND/OR branch-and-bound for computational protein design optimizing K.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

NeuroBE: Escalating neural network approximations of Bucket Elimination.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Be Like Water: Adaptive Floating Point for Machine Learning.
Proceedings of the International Conference on Machine Learning, 2022

Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks.
Proceedings of the International Conference on Machine Learning, 2022

2021
Temporal-Difference Value Estimation via Uncertainty-Guided Soft Updates.
CoRR, 2021

2020
A Deep Choice Model for Hiring Outcome Prediction in Online Labor Markets.
Int. J. Comput. Commun. Control, 2020

Multi-Lane Short-Term Traffic Forecasting With Convolutional LSTM Network.
IEEE Access, 2020

Active learning with RESSPECT: Resource allocation for extragalactic astronomical transients.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Scaling Up AND/OR Abstraction Sampling.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
A Weighted Mini-Bucket Bound for Solving Influence Diagram.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Empirical Study of MC-Dropout in Various Astronomical Observing Conditions.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Anytime Recursive Best-First Search for Bounding Marginal MAP.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
AND/OR Search for Marginal MAP.
J. Artif. Intell. Res., 2018

Estimating Warehouse Rental Price using Machine Learning Techniques.
Int. J. Comput. Commun. Control, 2018

Finite-sample Bounds for Marginal MAP.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Join Graph Decomposition Bounds for Influence Diagrams.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Abstraction Sampling in Graphical Models.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Lifted Weighted Mini-Bucket.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Stochastic Anytime Search for Bounding Marginal MAP.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

ContextNet: Deep learning for Star Galaxy Classification.
Proceedings of the 35th International Conference on Machine Learning, 2018

Accelerating Dynamic Programs via Nested Benders Decomposition with Application to Multi-Person Pose Estimation.
Proceedings of the Computer Vision - ECCV 2018, 2018

Anytime Anyspace AND/OR Best-First Search for Bounding Marginal MAP.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Generalized Dual Decomposition for Bounding Maximum Expected Utility of Influence Diagrams with Perfect Recall.
Proceedings of the Workshops of the The Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Lifted Generalized Dual Decomposition.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Multi-Person Pose Estimation via Column Generation.
CoRR, 2017

Dynamic Importance Sampling for Anytime Bounds of the Partition Function.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Belief Propagation in Conditional RBMs for Structured Prediction.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Anytime Anyspace AND/OR Search for Bounding the Partition Function.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Anytime Best+Depth-First Search for Bounding Marginal MAP.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Learning Infinite RBMs with Frank-Wolfe.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Cell-to-cell activity prediction for smart cities.
Proceedings of the IEEE Conference on Computer Communications Workshops, 2016

Deep neural networks for precipitation estimation from remotely sensed information.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

From Exact to Anytime Solutions for Marginal MAP.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Estimating the Partition Function by Discriminance Sampling.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Incremental Region Selection for Mini-bucket Elimination Bounds.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Decomposition Bounds for Marginal MAP.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Probabilistic Variational Bounds for Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Pushing Forward Marginal MAP with Best-First Search.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Boosting crowdsourcing with expert labels: Local vs. global effects.
Proceedings of the 18th International Conference on Information Fusion, 2015

2014
Optimizing redundant-data clustering for interactive walkthrough applications.
Vis. Comput., 2014

Beyond MAP Estimation With the Track-Oriented Multiple Hypothesis Tracker.
IEEE Trans. Signal Process., 2014

AND/OR Search for Marginal MAP.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Beyond Static Mini-Bucket: Towards Integrating with Iterative Cost-Shifting Based Dynamic Heuristics.
Proceedings of the Seventh Annual Symposium on Combinatorial Search, 2014

Distributed Estimation, Information Loss and Exponential Families.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Marginal Structured SVM with Hidden Variables.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Variational algorithms for marginal MAP.
J. Mach. Learn. Res., 2013

Scoring Workers in Crowdsourcing: How Many Control Questions are Enough?
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Variational Planning for Graph-based MDPs.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Image enhancement in projectors via optical pixel shift and overlay.
Proceedings of the IEEE International Conference on Computational Photography, 2013

Linear Approximation to ADMM for MAP inference.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Understanding Errors in Approximate Distributed Latent Dirichlet Allocation.
IEEE Trans. Knowl. Data Eng., 2012

A Cluster-Cumulant Expansion at the Fixed Points of Belief Propagation.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Belief Propagation for Structured Decision Making.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Join-graph based cost-shifting schemes.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

A graphical model representation of the track-oriented multiple hypothesis tracker.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Variational Inference for Crowdsourcing.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Distributed Parameter Estimation via Pseudo-likelihood .
Proceedings of the 29th International Conference on Machine Learning, 2012

Fast Planar Correlation Clustering for Image Segmentation.
Proceedings of the Computer Vision - ECCV 2012, 2012

Approximating the Sum Operation for Marginal-MAP Inference.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Fault Identification Via Nonparametric Belief Propagation.
IEEE Trans. Signal Process., 2011

Multicore Gibbs Sampling in Dense, Unstructured Graphs.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Adaptive Exact Inference in Graphical Models.
J. Mach. Learn. Res., 2011

Learning Scale Free Networks by Reweighted L1 regularization.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Revisiting MAP Estimation, Message Passing and Perfect Graphs.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Tightening MRF Relaxations with Planar Subproblems.
Proceedings of the UAI 2011, 2011

Planar Cycle Covering Graphs.
Proceedings of the UAI 2011, 2011

Bounding the Partition Function using Holder's Inequality.
Proceedings of the 28th International Conference on Machine Learning, 2011

Session MP3a: Graphical models in signal processing II.
Proceedings of the Conference Record of the Forty Fifth Asilomar Conference on Signals, 2011

Fast Parallel and Adaptive Updates for Dual-Decomposition Solvers.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Learning with Blocks: Composite Likelihood and Contrastive Divergence.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Nonparametric belief propagation.
Commun. ACM, 2010

Estimating replicate time shifts using Gaussian process regression.
Bioinform., 2010

Negative Tree Reweighted Belief Propagation.
Proceedings of the UAI 2010, 2010

Particle Filtered MCMC-MLE with Connections to Contrastive Divergence.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Covering trees and lower-bounds on quadratic assignment.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009
Particle Belief Propagation.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Distributed Fault Identification via Non-parametric Belief Propagation
CoRR, 2009

A Low Density Lattice Decoder via Non-Parametric Belief Propagation
CoRR, 2009

Bayesian detection of non-sinusoidal periodic patterns in circadian expression data.
Bioinform., 2009

Particle-based Variational Inference for Continuous Systems.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

A low density lattice decoder via non-parametric belief propagation.
Proceedings of the 47th Annual Allerton Conference on Communication, 2009

2008
Adaptive inference on general graphical models.
Proceedings of the UAI 2008, 2008

Fast collapsed gibbs sampling for latent dirichlet allocation.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Probabilistic Analysis of a Large-Scale Urban Traffic Sensor Data Set.
Proceedings of the Knowledge Discovery from Sensor Data, 2008

2007
Learning to detect events with Markov-modulated poisson processes.
ACM Trans. Knowl. Discov. Data, 2007

Accuracy Bounds for Belief Propagation.
Proceedings of the UAI 2007, 2007

Efficient Bayesian Inference for Dynamically Changing Graphs.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Distributed fusion in sensor networks.
IEEE Signal Process. Mag., 2006

Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation.
Proceedings of the UAI '06, 2006

Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Adaptive event detection with time-varying poisson processes.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

2005
Inference in sensor networks: graphical models and particle methods.
PhD thesis, 2005

Nonparametric belief propagation for self-localization of sensor networks.
IEEE J. Sel. Areas Commun., 2005

Loopy Belief Propagation: Convergence and Effects of Message Errors.
J. Mach. Learn. Res., 2005

Estimating dependency and significance for high-dimensional data.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Nonparametric hypothesis tests for statistical dependency.
IEEE Trans. Signal Process., 2004

Message Errors in Belief Propagation.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Nonparametric belief propagation for self-calibration in sensor networks.
Proceedings of the Third International Symposium on Information Processing in Sensor Networks, 2004

Nonparametric belief propagation for sensor self-calibration.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

2003
Efficient Multiscale Sampling from Products of Gaussian Mixtures.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Hypothesis Testing over Factorizations for Data Association.
Proceedings of the Information Processing in Sensor Networks, 2003

Nonparametric Belief Propagation.
Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2003), 2003

2001
Nonparametric estimators for online signature authentication.
Proceedings of the IEEE International Conference on Acoustics, 2001

1999
Learning Informative Statistics: A Nonparametnic Approach.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999


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