Brian Kulis

15.2k citations

53 papers · 7.5k indexed · 8 hit papers · h-index 28

Impact in

Computer Vision and Pattern Recognition top 0.1%
- Advanced Image and Video Retrieval Techniques
- Face and Expression Recognition
- Video Surveillance and Tracking Methods
- Image Retrieval and Classification Techniques
- Multimodal Machine Learning Applications
Artificial Intelligence top 0.2%
- Domain Adaptation and Few-Shot Learning
- Advanced Clustering Algorithms Research

Papers in

Computational Mathematics 1
Computer Vision and Pattern Recognition 27
- Face and Expression Recognition 11
- Advanced Image and Video Retrieval Techniques 11
- Multimodal Machine Learning Applications 7

Co-authors: Inderjit S. Dhillon Kristen Grauman Yuqiang Guan Trevor Darrell Prateek Jain Jason V. Davis Suvrit Sra Kate Saenko
Journals: IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)Journal of Machine Learning Research (2 papers)Machine Learning (1 paper)IEEE Transactions on Parallel and Distributed Systems (1 paper)International Journal of Computer Vision (1 paper)
Partner nations: United States Germany India

In The Last Decade

Brian Kulis

51 papers receiving 7.3k citations

Hit Papers

8 papers align trajectories log scale

Metric Learning: A Survey 2013 · 290 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2013 now publishers, Inc. eBooks
2013 Metric Learning: A Survey
2011 What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
2009 Kernelized locality-sensitive hashing for scalable image search
2009 UC Berkeley
2007 Information-theoretic metric learning
2007 IEEE Transactions on Pattern Analysis and Machine Intelligence
2004 Kernel k-means

Peers

Countries citing papers authored by Brian Kulis

Since Specialization

Citations

This map shows the geographic impact of Brian Kulis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Brian Kulis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Kulis more than expected).

Fields of papers citing papers by Brian Kulis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian Kulis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Brian Kulis. The network helps show where Brian Kulis may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Brian Kulis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Brian Kulis Line = papers co-authored together Brian Kulis links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning IEEE Transactions on Parallel and Distributed Systems ·Dubin Ba, 杨文丽, Benjamin Schwaller, Phil Labuschagne, Vitus J. Leung, Jim Brandt, Brian Kulis, Manuel Egele, Ayse K. Coskun	2024	5
2	Descriptor and Word Soups Q: Overcoming the Parameter Efficiency Accuracy Tradeoff for Out-of-Distribution Few-shot Learning OpenBU (Boston University) ·程延伟, Theodoros Tsiligkaridis, Brian Kulis	2024	0
3	Prodigy: Towards Unsupervised Anomaly Detection in Production HPC Systems Dubin Ba, 杨文丽, Benjamin Schwaller, Phil Labuschagne, Vitus J. Leung, Jim Brandt, Brian Kulis, Manuel Egele, Ayse K. Coskun	2023	4
4	Substitutional Neural Image Compression OpenBU (Boston University) ·Xiao Wang, Н К Адамадзиева, Wei Jiang, Wei Wang, Xiaozhong Xu, Shan Liu, Brian Kulis, Peter Chin	2022	5
5	Learning Bregman Divergences. arXiv (Cornell University) ·SimonMary Asese Aihiokhai, Venkatesh Saligrama, David A. Castañón, Brian Kulis	2019	1
6	Stable Distribution Alignment Using the Dual of the Adversarial Distance International Conference on Learning Representations ·Ben Usman, Kate Saenko, Brian Kulis	2018	1
7	Small-Variance Asymptotics for Hidden Markov Models Neural Information Processing Systems ·Anirban Roychowdhury, 郭雅希, Brian Kulis	2013	8
8	Metric and kernel learning using a linear transformation Journal of Machine Learning Research ·Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon	2012	116
9	Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models Neural Information Processing Systems ·郭雅希, Brian Kulis, Michael I. Jordan	2012	28
10	Metric learning for reinforcement learning agents Adaptive Agents and Multi-Agents Systems ·Matthew E. Taylor, Brian Kulis, Fei Sha	2011	13
11	Kernelized Locality-Sensitive Hashing IEEE Transactions on Pattern Analysis and Machine Intelligence ·Brian Kulis, Kristen Grauman	2011	247
12	Inductive Regularized Learning of Kernel Functions neural information processing systems ·Prateek Jain, Brian Kulis, Inderjit S. Dhillon	2010	28
13	Convex Perturbations for Scalable Semidefinite Programming Max Planck Institute for Plasma Physics ·Brian Kulis, Suvrit Sra, Inderjit S. Dhillon	2009	6
14	Learning to Hash with Binary Reconstructive Embeddings UC Berkeley ·Brian Kulis, Trevor Darrell Hit paper breakdown →	2009	534
15	Low-Rank Kernel Learning with Bregman Matrix Divergences Journal of Machine Learning Research ·Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon	2009	151
16	Kernelized locality-sensitive hashing for scalable image search Brian Kulis, Kristen Grauman Hit paper breakdown →	2009	620
17	Online Metric Learning and Fast Similarity Search Neural Information Processing Systems ·Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman	2008	125
18	Fast Low-Rank Semidefinite Programming for Embedding and Clustering International Conference on Artificial Intelligence and Statistics ·Brian Kulis, Xin Tian, John Platt	2007	31
19	Weighted Graph Cuts without Eigenvectors A Multilevel Approach IEEE Transactions on Pattern Analysis and Machine Intelligence ·Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis Hit paper breakdown →	2007	635
20	Information-theoretic Metric Learning MPG.PuRe (Max Planck Society) ·Jason V. Davis, Brian Kulis, Inderjit S. Dhillon	2006	25

About Brian Kulis

Brian Kulis is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition, Artificial Intelligence, Structural Biology and Statistical and Nonlinear Physics, having authored 53 papers that have together received 7.5k indexed citations. Recurring topics across this work include Face and Expression Recognition (11 papers), Advanced Image and Video Retrieval Techniques (11 papers), Machine Learning and Algorithms (10 papers), Advanced Clustering Algorithms Research (10 papers), Domain Adaptation and Few-Shot Learning (10 papers), Sparse and Compressive Sensing Techniques (8 papers), Multimodal Machine Learning Applications (7 papers) and Complex Network Analysis Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.0k citations), Artificial Intelligence (3.4k citations), Signal Processing (670 citations), Statistical and Nonlinear Physics (717 citations) and Media Technology (460 citations). Brian Kulis has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Inderjit S. Dhillon, Kristen Grauman, Yuqiang Guan, Trevor Darrell, Prateek Jain, Jason V. Davis, Suvrit Sra, Kate Saenko, Michael I. Jordan and Prateek Jain. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Machine Learning Research, Machine Learning, IEEE Transactions on Parallel and Distributed Systems and International Journal of Computer Vision.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact