Erik G. Learned-Miller

According to our database, Erik G. Learned-Miller authored at least 132 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields.

Pia Bideau, Erik G. Learned-Miller, Cordelia Schmid, Karteek Alahari

Int. J. Comput. Vis., January, 2024

Tracklet-based Explainable Video Anomaly Localization.

Ashish Singh, Michael J. Jones, Erik G. Learned-Miller

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

A domain-agnostic approach for characterization of lifelong learning systems.

Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha

Neural Networks, March, 2023

Log-Concavity of Multinomial Likelihood Functions Under Interval Censoring Constraints on Frequencies or Their Partial Sums.

Bruce Levin, Erik G. Learned-Miller

CoRR, 2023

An Efficient General-Purpose Modular Vision Model via Multi-Task Heterogeneous Training.

Zitian Chen, Mingyu Ding, Yikang Shen, Wei Zhan, Masayoshi Tomizuka, Erik G. Learned-Miller, Chuang Gan

CoRR, 2023

DCVNet: Dilated Cost Volume Networks for Fast Optical Flow.

Huaizu Jiang, Erik G. Learned-Miller

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging.

Ke Xiao, Erik G. Learned-Miller, Evangelos Kalogerakis, James Priest, Madalina Fiterau

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Event Camera-Based Visual Odometry for Dynamic Motion Tracking of a Legged Robot Using Adaptive Time Surface.

Shifan Zhu, Zhipeng Tang, Michael Yang, Erik G. Learned-Miller, Donghyun Kim

IROS, 2023

Robust Frame-to-Frame Camera Rotation Estimation in Crowded Scenes.

Fabien Delattre, David Dirnfeld, Phat Nguyen, Stephen Scarano, Michael J. Jones, Pedro Miraldo, Erik G. Learned-Miller

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Inv-Senet: Invariant Self Expression Network for Clustering Under Biased Data.

Ashutosh Singh, Ashish Singh, Aria Masoomi, Tales Imbiriba, Erik G. Learned-Miller, Deniz Erdogmus

Proceedings of the IEEE International Conference on Acoustics, 2023

EVAL: Explainable Video Anomaly Localization.

Ashish Singh, Michael J. Jones, Erik G. Learned-Miller

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners.

Zitian Chen, Yikang Shen, Mingyu Ding, Zhenfang Chen, Hengshuang Zhao, Erik G. Learned-Miller, Chuang Gan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Mod-Squad: Designing Mixture of Experts As Modular Multi-Task Learners.

Zitian Chen, Yikang Shen, Mingyu Ding, Zhenfang Chen, Hengshuang Zhao, Erik G. Learned-Miller, Chuang Gan

CoRR, 2022

Inv-SENnet: Invariant Self Expression Network for clustering under biased data.

Ashutosh Singh, Ashish Singh, Aria Masoomi, Tales Imbiriba, Erik G. Learned-Miller, Deniz Erdogmus

CoRR, 2022

PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud Segmentation.

Gopal Sharma, Bidya Dash, Aruni Roy Chowdhury, Matheus Gadelha, Marios Loizou, Liangliang Cao, Rui Wang, Erik G. Learned-Miller, Subhransu Maji, Evangelos Kalogerakis

Comput. Graph. Forum, 2022

Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain Images.

Tejas Panambur, Deep Chakraborty, Melissa Meyer, Ralph Milliken, Erik G. Learned-Miller, Mario Parente

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Image registration: Maximum likelihood, minimum entropy and deep learning.

Alireza Sedghi, Lauren J. O'Donnell, Tina Kapur, Erik G. Learned-Miller, Parvin Mousavi, William M. Wells III

Medical Image Anal., 2021

SurFit: Learning to Fit Surfaces Improves Few Shot Learning on Point Clouds.

Gopal Sharma, Bidya Dash, Matheus Gadelha, Aruni RoyChowdhury, Marios Loizou, Evangelos Kalogerakis, Liangliang Cao, Erik G. Learned-Miller, Rui Wang, Subhransu Maji

CoRR, 2021

Passage Retrieval for Outside-Knowledge Visual Question Answering.

Chen Qu, Hamed Zamani, Liu Yang, W. Bruce Croft, Erik G. Learned-Miller

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Universal Off-Policy Evaluation.

Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Practical Mean Bounds for Small Samples.

My Phan, Philip S. Thomas, Erik G. Learned-Miller

Proceedings of the 38th International Conference on Machine Learning, 2021

The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data.

Cheng Gu, Erik G. Learned-Miller, Daniel Sheldon, Guillermo Gallego, Pia Bideau

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Shot in the Dark: Few-Shot Learning With No Base-Class Labels.

Zitian Chen, Subhransu Maji, Erik G. Learned-Miller

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

SID-NISM: A Self-supervised Low-light Image Enhancement Framework.

Lijun Zhang, Xiao Liu, Erik G. Learned-Miller, Hui Guan

CoRR, 2020

Cross-Supervised Object Detection.

Zitian Chen, Zhiqiang Shen, Jiahui Yu, Erik G. Learned-Miller

CoRR, 2020

C-14: assured timestamps for drone videos.

Zhipeng Tang, Fabien Delattre, Pia Bideau, Mark D. Corner, Erik G. Learned-Miller

Proceedings of the MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking, 2020

Improving Face Recognition by Clustering Unlabeled Faces in the Wild.

Aruni RoyChowdhury, Xiang Yu, Kihyuk Sohn, Erik G. Learned-Miller, Manmohan Chandraker

Proceedings of the Computer Vision - ECCV 2020, 2020

Label-Efficient Learning on Point Clouds Using Approximate Convex Decompositions.

Matheus Gadelha, Aruni RoyChowdhury, Gopal Sharma, Evangelos Kalogerakis, Liangliang Cao, Erik G. Learned-Miller, Rui Wang, Subhransu Maji

Proceedings of the Computer Vision - ECCV 2020, 2020

Zero-Shot Learning in the Presence of Hierarchically Coarsened Labels.

Colin Samplawski, Erik G. Learned-Miller, Heesung Kwon, Benjamin M. Marlin

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

In Defense of Grid Features for Visual Question Answering.

Huaizu Jiang, Ishan Misra, Marcus Rohrbach, Erik G. Learned-Miller, Xinlei Chen

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Server-Side Traffic Analysis Reveals Mobile Location Information over the Internet.

Keen Sung, Joydeep Biswas, Erik G. Learned-Miller, Brian Neil Levine, Marc Liberatore

IEEE Trans. Mob. Comput., 2019

A New Confidence Interval for the Mean of a Bounded Random Variable.

Erik G. Learned-Miller, Philip S. Thomas

CoRR, 2019

Integrating Propositional and Relational Label Side Information for Hierarchical Zero-Shot Image Classification.

Colin Samplawski, Heesung Kwon, Erik G. Learned-Miller, Benjamin M. Marlin

CoRR, 2019

Concentration Inequalities for Conditional Value at Risk.

Philip S. Thomas, Erik G. Learned-Miller

Proceedings of the 36th International Conference on Machine Learning, 2019

SENSE: A Shared Encoder Network for Scene-Flow Estimation.

Huaizu Jiang, Deqing Sun, Varun Jampani, Zhaoyang Lv, Erik G. Learned-Miller, Jan Kautz

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Pixel-Adaptive Convolutional Neural Networks.

Hang Su, Varun Jampani, Deqing Sun, Orazio Gallo, Erik G. Learned-Miller, Jan Kautz

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Half&Half: New Tasks and Benchmarks for Studying Visual Common Sense.

Ashish Singh, Hang Su, SouYoung Jin, Huaizu Jiang, Chetan Manjesh, Geng Luo, Ziwei He, Li Hong, Erik G. Learned-Miller, Rosie Cowell

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Automatic Adaptation of Object Detectors to New Domains Using Self-Training.

Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik G. Learned-Miller

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Citation Worthiness of Sentences in Scientific Reports.

Hamed R. Bonab, Hamed Zamani, Erik G. Learned-Miller, James Allan

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Learning to Use a Ratchet by Modeling Spatial Relations in Demonstrations.

Li Yang Ku, Scott Michael Jordan, Julia Badger, Erik G. Learned-Miller, Rod Grupen

Proceedings of the 2018 International Symposium on Experimental Robotics, 2018

A Framework for Dexterous Manipulation.

Li Yang Ku, Jonathan Rogers, Philip Strawser, Julia Badger, Erik G. Learned-Miller, Rod Grupen

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Unsupervised Hard Example Mining from Videos for Improved Object Detection.

SouYoung Jin, Aruni RoyChowdhury, Huaizu Jiang, Ashish Singh, Aditya Prasad, Deep Chakraborty, Erik G. Learned-Miller

Proceedings of the Computer Vision - ECCV 2018, 2018

Self-Supervised Relative Depth Learning for Urban Scene Understanding.

Huaizu Jiang, Gustav Larsson, Michael Maire, Greg Shakhnarovich, Erik G. Learned-Miller

Proceedings of the Computer Vision - ECCV 2018, 2018

MoA-Net: Self-supervised Motion Segmentation.

Pia Bideau, Rakesh R. Menon, Erik G. Learned-Miller

Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation.

Huaizu Jiang, Deqing Sun, Varun Jampani, Ming-Hsuan Yang, Erik G. Learned-Miller, Jan Kautz

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

The Best of Both Worlds: Combining CNNs and Geometric Constraints for Hierarchical Motion Segmentation.

Pia Bideau, Aruni RoyChowdhury, Rakesh R. Menon, Erik G. Learned-Miller

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

From Neural Re-Ranking to Neural Ranking: Learning a Sparse Representation for Inverted Indexing.

Hamed Zamani, Mostafa Dehghani, W. Bruce Croft, Erik G. Learned-Miller, Jaap Kamps

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

Guest Editorial: Best of CVPR 2015.

Kristen Grauman, Erik G. Learned-Miller, Antonio Torralba, Andrew Zisserman

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Self-Supervised Depth Learning for Urban Scene Understanding.

Huaizu Jiang, Erik G. Learned-Miller, Gustav Larsson, Michael Maire, Greg Shakhnarovich

CoRR, 2017

Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples.

Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum

CoRR, 2017

Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples.

Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Associating grasp configurations with hierarchical features in convolutional neural networks.

Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

An aspect representation for object manipulation based on convolutional neural networks.

Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

End-to-End Face Detection and Cast Grouping in Movies Using Erdös-Rényi Clustering.

Sou-Young Jin, Hang Su, Chris Stauffer, Erik G. Learned-Miller

Proceedings of the IEEE International Conference on Computer Vision, 2017

Face Detection with the Faster R-CNN.

Huaizu Jiang, Erik G. Learned-Miller

Proceedings of the 12th IEEE International Conference on Automatic Face & Gesture Recognition, 2017

2016

Associating Grasping with Convolutional Neural Network Features.

Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen

CoRR, 2016

A Detailed Rubric for Motion Segmentation.

Pia Bideau, Erik G. Learned-Miller

CoRR, 2016

One-to-many face recognition with bilinear CNNs.

Aruni Roy Chowdhury, Tsung-Yu Lin, Subhransu Maji, Erik G. Learned-Miller

Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016

It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos.

Pia Bideau, Erik G. Learned-Miller

Proceedings of the Computer Vision - ECCV 2016, 2016

Distinguishing Weather Phenomena from Bird Migration Patterns in Radar Imagery.

Aruni Roy Chowdhury, Daniel Sheldon, Subhransu Maji, Erik G. Learned-Miller

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

Large-Scale 3D Shape Retrieval from ShapeNet Core55.

Manolis Savva, Fisher Yu, Hao Su, Masaki Aono, Baoquan Chen, Daniel Cohen-Or, Weihong Deng, Hang Su, Song Bai, Xiang Bai, Noa Fish, Jiajie Han, Evangelos Kalogerakis, Erik G. Learned-Miller, Yangyan Li, Minghui Liao, Subhransu Maji, Atsushi Tatsuma, Yida Wang, Nanhai Zhang, Zhichao Zhou

Proceedings of the 9th Eurographics Workshop on 3D Object Retrieval, 2016

2015

Face Identification with Bilinear CNNs.

Aruni RoyChowdhury, Tsung-Yu Lin, Subhransu Maji, Erik G. Learned-Miller

CoRR, 2015

Modeling Objects as Aspect Transition Graphs to Support Manipulation.

Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen

Proceedings of the Robotics Research, 2015

Multi-view Convolutional Neural Networks for 3D Shape Recognition.

Hang Su, Subhransu Maji, Evangelos Kalogerakis, Erik G. Learned-Miller

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Error detection and surprise in stochastic robot actions.

Li Yang Ku, Dirk Ruiken, Erik G. Learned-Miller, Roderic A. Grupen

Proceedings of the 15th IEEE-RAS International Conference on Humanoid Robots, 2015

2014

Background subtraction: separating the modeling and the inference.

Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller

Mach. Vis. Appl., 2014

Optical Flow Estimation with Channel Constancy.

Laura Sevilla-Lara, Deqing Sun, Erik G. Learned-Miller, Michael J. Black

Proceedings of the Computer Vision - ECCV 2014, 2014

The Aspect Transition Graph: An Affordance-Based Model.

Li Yang Ku, Shiraj Sen, Erik G. Learned-Miller, Roderic A. Grupen

Proceedings of the Computer Vision - ECCV 2014 Workshops, 2014

The Shape-Time Random Field for Semantic Video Labeling.

Andrew Kae, Benjamin M. Marlin, Erik G. Learned-Miller

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Half-Wits: Software Techniques for Low-Voltage Probabilistic Storage on Microcontrollers with NOR Flash Memory.

Mastooreh Salajegheh, Yue Wang, Anxiao Jiang, Erik G. Learned-Miller, Kevin Fu

ACM Trans. Embed. Comput. Syst., 2013

Turning Off GPS Is Not Enough: Cellular Location Leaks over the Internet.

Hamed Soroush, Keen Sung, Erik G. Learned-Miller, Brian Neil Levine, Marc Liberatore

Proceedings of the Privacy Enhancing Technologies - 13th International Symposium, 2013

Scene Text Segmentation via Inverse Rendering.

Yahan Zhou, Jacqueline L. Feild, Erik G. Learned-Miller, Rui Wang

Proceedings of the 12th International Conference on Document Analysis and Recognition, 2013

Using a Probabilistic Syllable Model to Improve Scene Text Recognition.

Jacqueline L. Feild, Erik G. Learned-Miller, David A. Smith

Proceedings of the 12th International Conference on Document Analysis and Recognition, 2013

Improving Open-Vocabulary Scene Text Recognition.

Jacqueline L. Feild, Erik G. Learned-Miller

Proceedings of the 12th International Conference on Document Analysis and Recognition, 2013

Coherent Motion Segmentation in Moving Camera Videos Using Optical Flow Orientations.

Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller

Proceedings of the IEEE International Conference on Computer Vision, 2013

Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling.

Andrew Kae, Kihyuk Sohn, Honglak Lee, Erik G. Learned-Miller

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

Distribution Fields with Adaptive Kernels for Large Displacement Image Alignment.

Benjamin Mears, Laura Sevilla-Lara, Erik G. Learned-Miller

Proceedings of the British Machine Vision Conference, 2013

2012

Bounding the Probability of Error for High Precision Optical Character Recognition.

Gary B. Huang, Andrew Kae, Carl Doersch, Erik G. Learned-Miller

J. Mach. Learn. Res., 2012

Unsupervised Joint Alignment and Clustering using Bayesian Nonparametrics.

Marwan A. Mattar, Allen R. Hanson, Erik G. Learned-Miller

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Learning to Align from Scratch.

Gary B. Huang, Marwan A. Mattar, Honglak Lee, Erik G. Learned-Miller

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

Distribution fields for tracking.

Laura Sevilla-Lara, Erik G. Learned-Miller

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Background modeling using adaptive pixelwise kernel variances in a hybrid feature space.

Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Learning hierarchical representations for face verification with convolutional deep belief networks.

Gary B. Huang, Honglak Lee, Erik G. Learned-Miller

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Improvements in Joint Domain-Range Modeling for Background Subtraction.

Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller

Proceedings of the British Machine Vision Conference, 2012

2011

Introduction to the Special Section on Real-World Face Recognition.

Gang Hua, Ming-Hsuan Yang, Erik G. Learned-Miller, Yi Ma, Matthew A. Turk, David J. Kriegman, Thomas S. Huang

IEEE Trans. Pattern Anal. Mach. Intell., 2011

Learning on the fly: a font-free approach toward multilingual OCR.

Andrew Kae, David A. Smith, Erik G. Learned-Miller

Int. J. Document Anal. Recognit., 2011

Forensic Triage for Mobile Phones with DEC0DE.

Robert J. Walls, Erik G. Learned-Miller, Brian Neil Levine

Proceedings of the 20th USENIX Security Symposium, 2011

Exploiting Half-Wits: Smarter Storage for Low-Power Devices.

Mastooreh Salajegheh, Yue Wang, Kevin Fu, Anxiao Jiang, Erik G. Learned-Miller

Proceedings of the 9th USENIX Conference on File and Storage Technologies, 2011

Enforcing similarity constraints with integer programming for better scene text recognition.

David L. Smith, Jacqueline L. Feild, Erik G. Learned-Miller

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

Online domain adaptation of a pre-trained cascade of classifiers.

Vidit Jain, Erik G. Learned-Miller

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Improving state-of-the-art OCR through high-precision document-specific modeling.

Andrew Kae, Gary B. Huang, Carl Doersch, Erik G. Learned-Miller

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Learning class-specific image transformations with higher-order Boltzmann machines.

Gary B. Huang, Erik G. Learned-Miller

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010

Reverse engineering for mobile systems forensics with Ares.

John Tuttle, Robert J. Walls, Erik G. Learned-Miller, Brian Neil Levine

Proceedings of the 2010 ACM workshop on Insider threats, Insider Threats '10, Chicago, 2010

2009

Scene Text Recognition Using Similarity and a Lexicon with Sparse Belief Propagation.

Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson

IEEE Trans. Pattern Anal. Mach. Intell., 2009

Bounding the Probability of Error for High Precision Recognition

Andrew Kae, Gary B. Huang, Erik G. Learned-Miller

CoRR, 2009

Learning on the Fly: Font-Free Approaches to Difficult OCR Problems.

Andrew Kae, Erik G. Learned-Miller

Proceedings of the 10th International Conference on Document Analysis and Recognition, 2009

Nonparametric curve alignment.

Marwan A. Mattar, Michael G. Ross, Erik G. Learned-Miller

Proceedings of the IEEE International Conference on Acoustics, 2009

2008

A Probabilistic Upper Bound on Differential Entropy.

Erik G. Learned-Miller, Joseph DeStefano

IEEE Trans. Inf. Theory, 2008

Learning to Locate Informative Features for Visual Identification.

Andras Ferencz, Erik G. Learned-Miller, Jitendra Malik

Int. J. Comput. Vis., 2008

A discriminative semi-Markov model for robust scene text recognition.

Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Towards unconstrained face recognition.

Gary B. Huang, Manjunath Narayana, Erik G. Learned-Miller

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008

2007

Analyzing <i>in situ</i> gene expression in the mouse brain with image registration, feature extraction and block clustering.

Manjunatha Jagalur, Chris Pal, Erik G. Learned-Miller, R. Thomas Zoeller, David Kulp

BMC Bioinform., 2007

Techniques and Applications for Persistent Backgrounding in a Humanoid Torso Robot.

David Walker Duhon, Jerod J. Weinman, Erik G. Learned-Miller

Proceedings of the 2007 IEEE International Conference on Robotics and Automation, 2007

Context-Sensitive Error Correction: Using Topic Models to Improve OCR.

Michael L. Wick, Michael G. Ross, Erik G. Learned-Miller

Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR 2007), 2007

Fast Lexicon-Based Scene Text Recognition with Sparse Belief Propagation.

Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson

Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR 2007), 2007

Cryptogram Decoding for OCR Using Numerization Strings.

Gary B. Huang, Erik G. Learned-Miller, Andrew McCallum

Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR 2007), 2007

People-LDA: Anchoring Topics to People using Face Recognition.

Vidit Jain, Erik G. Learned-Miller, Andrew McCallum

Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

Unsupervised Joint Alignment of Complex Images.

Gary B. Huang, Vidit Jain, Erik G. Learned-Miller

Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

2006

Data Driven Image Models through Continuous Joint Alignment.

Erik G. Learned-Miller

IEEE Trans. Pattern Anal. Mach. Intell., 2006

Detecting Acromegaly: Screening for Disease with a Morphable Model.

Erik G. Learned-Miller, Qifeng Lu, Angela Paisley, Peter Trainer, Volker Blanz, Katrin Dedden, Ralph Miller

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2006

Combinatorial Markov Random Fields.

Ron Bekkerman, Mehran Sahami, Erik G. Learned-Miller

Proceedings of the Machine Learning: ECML 2006, 2006

Improving Recognition of Novel Input with Similarity.

Jerod J. Weinman, Erik G. Learned-Miller

Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006

Discriminative Training of Hyper-feature Models for Object Identification.

Vidit Jain, Andras Ferencz, Erik G. Learned-Miller

Proceedings of the British Machine Vision Conference 2006, 2006

2005

Many Heads Are Better Than One: Jointly Removing Bias from Multiple MRIs Using Nonparametric Maximum Likelihood.

Erik G. Learned-Miller, Vidit Jain

Proceedings of the Information Processing in Medical Imaging, 2005

Building a Classification Cascade for Visual Identification from One Example.

Andras Ferencz, Erik G. Learned-Miller, Jitendra Malik

Proceedings of the 10th IEEE International Conference on Computer Vision (ICCV 2005), 2005

Sign Classification using Local and Meta-Features.

Marwan A. Mattar, Allen R. Hanson, Erik G. Learned-Miller

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005

Combining Local and Global Image Features for Object Class Recognition.

Dimitri A. Lisin, Marwan A. Mattar, Matthew B. Blaschko, Erik G. Learned-Miller, Mark C. Benfield

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005

Efficient Population Registration of 3D Data.

Lilla Zöllei, Erik G. Learned-Miller, W. Eric L. Grimson, William M. Wells III

Proceedings of the Computer Vision for Biomedical Image Applications, 2005

2004

Joint MRI Bias Removal Using Entropy Minimization Across Images.

Erik G. Learned-Miller, Parvez Ahammad

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Learning Hyper-Features for Visual Identification.

Andras Ferencz, Erik G. Learned-Miller, Jitendra Malik

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Names and Faces in the News.

Tamara L. Berg, Alexander C. Berg, Jaety Edwards, Michael Maire, Ryan White, Yee Whye Teh, Erik G. Learned-Miller, David A. Forsyth

Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2004), with CD-ROM, 27 June, 2004

2003

ICA Using Spacings Estimates of Entropy.

Erik G. Learned-Miller, John W. Fisher III

J. Mach. Learn. Res., 2003

A new class of entropy estimators for multi-dimensional densities.

Erik G. Miller

Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Practical Non-parametric Density Estimation on a Transformation Group for Vision.

Erik G. Miller, Christophe Chefd'Hotel

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

2002

Learning from one example in machine vision by sharing probability densities.

Erik Gundersen Miller

PhD thesis, 2002

Unsupervised Color Constancy.

Kinh Tieu, Erik G. Miller

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001

Transform-invariant Image Decomposition with Similarity Templates.

Chris Stauffer, Erik G. Miller, Kinh Tieu

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

A Binary Entropy Measure to Assess Nonrigid Registration Algorithms.

Simon K. Warfield, Jan Rexilius, Petra S. Huppi, Terrie E. Inder, Erik G. Miller, William M. Wells III, Gary P. Zientara, Ferenc A. Jolesz, Ron Kikinis

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2001

Color Eigenflows: Statistical Modeling of Joint Color Changes.

Erik G. Miller, Kinh Tieu

Proceedings of the Eighth International Conference On Computer Vision (ICCV-01), Vancouver, British Columbia, Canada, July 7-14, 2001, 2001

2000

Learning from One Example through Shared Densities on Transforms.

Erik G. Miller, Nicholas E. Matsakis, Paul A. Viola

Proceedings of the 2000 Conference on Computer Vision and Pattern Recognition (CVPR 2000), 2000

1999

Alternative Tilings for Improved Surface Area Estimates by Local Counting Algorithms.

Erik G. Miller

Comput. Vis. Image Underst., 1999

1998

Ambiguity and Constraint in Mathematical Expression Recognition.

Erik G. Miller, Paul A. Viola

Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998