Brian Kulis - RankMe

95 papers A* 22A 14C 5Misc 1Journal 39Unranked 14

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Image-Caption Encoding for Improving Zero-Shot Generalization. WACV Eric Yang Yu, Christopher Liao, Sathvik Ravi, Theodoros Tsiligkaridis, Brian Kulis
2025	C	`conf`	Job Grouping Based Intelligent Resource Prediction Framework. JSSPP Beste Oztop, Benjamin Schwaller, Vitus J. Leung, Jim M. Brandt, Brian Kulis, Manuel Egele, Ayse K. Coskun
2025	A*	`conf`	Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality Gap. ICLR Christopher Liao, Christian So, Theodoros Tsiligkaridis, Brian Kulis
2025	C	`conf`	Refine: A Robust Approach to Unsupervised Anomaly Detection for Production HPC Systems. ISC Efe Sencan, Yin-Ching Lee, Connor Casey, Benjamin Schwaller, Vitus J. Leung, Jim M. Brandt, Brian Kulis, Manuel Egele, Ayse K. Coskun
2024	J	`jnl`	A Data Centric Approach for Unsupervised Domain Generalization via Retrieval from Web Scale Multimodal Data. CoRR Christopher Liao, Theodoros Tsiligkaridis, Brian Kulis
2024	A*	`conf`	Descriptor and Word Soups Q: Overcoming the Parameter Efficiency Accuracy Tradeoff for Out-of-Distribution Few-shot Learning. CVPR Christopher Liao, Theodoros Tsiligkaridis, Brian Kulis
2024	J	`jnl`	Image-Caption Encoding for Improving Zero-Shot Generalization. CoRR Eric Yang Yu, Christopher Liao, Sathvik Ravi, Theodoros Tsiligkaridis, Brian Kulis
2024	Misc	`conf`	Maximum-Entropy Adversarial Audio Augmentation for Keyword Spotting. ICASSP Zuzhao Ye, Gregory Ciccarelli, Brian Kulis
2024	J	`jnl`	Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning. IEEE Trans. Parallel Distributed Syst. Burak Aksar, Efe Sencan, Benjamin Schwaller, Omar Aaziz, Vitus J. Leung, Jim M. Brandt, Brian Kulis, Manuel Egele, Ayse K. Coskun
2024	J	`jnl`	The NeurIPS 2023 Machine Learning for Audio Workshop: Affective Audio Benchmarks and Novel Data. CoRR Alice Baird, Rachel Manzelli, Panagiotis Tzirakis, Chris Gagne, Haoqi Li, Sadie Allen, Sander Dieleman, Brian Kulis, Shrikanth S. Narayanan, Alan Cowen
2023	J	`jnl`	Descriptor and Word Soups: Overcoming the Parameter Efficiency Accuracy Tradeoff for Out-of-Distribution Few-shot Learning. CoRR Christopher Liao, Theodoros Tsiligkaridis, Brian Kulis
2023	A	`conf`	Prodigy: Towards Unsupervised Anomaly Detection in Production HPC Systems. SC Burak Aksar, Efe Sencan, Benjamin Schwaller, Omar Aaziz, Vitus J. Leung, Jim M. Brandt, Brian Kulis, Manuel Egele, Ayse K. Coskun
2023	A*	`conf`	Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimization. ICML Christopher Liao, Theodoros Tsiligkaridis, Brian Kulis
2022	C	`conf`	ALBADross: Active Learning Based Anomaly Diagnosis for Production HPC Systems. CLUSTER Burak Aksar, Efe Sencan, Benjamin Schwaller, Omar Aaziz, Vitus J. Leung, Jim M. Brandt, Brian Kulis, Ayse K. Coskun
2022	A*	`conf`	Faster Algorithms for Learning Convex Functions. ICML Ali Siahkamari, Durmus Alp Emre Acar, Christopher Liao, Kelly L. Geyer, Venkatesh Saligrama, Brian Kulis
2022	A	`conf`	Latency Control for Keyword Spotting. INTERSPEECH Christin Jose, Joe Wang, Grant P. Strimel, Mohammad Omar Khursheed, Yuriy Mishchenko, Brian Kulis
2022	J	`jnl`	Latency Control for Keyword Spotting. CoRR Christin Jose, Joseph Wang, Grant P. Strimel, Mohammad Omar Khursheed, Yuriy Mishchenko, Brian Kulis
2022	J	`jnl`	Pick up the PACE: Fast and Simple Domain Adaptation via Ensemble Pseudo-Labeling. CoRR Christopher Liao, Theodoros Tsiligkaridis, Brian Kulis
2022	C	`conf`	Substitutional Neural Image Compression. PCS Xiao Wang, Ding Ding, Wei Jiang, Wei Wang, Xiaozhong Xu, Shan Liu, Brian Kulis, Peter Chin
2022	J	`jnl`	Supervised Metric Learning for Retrieval via Contextual Similarity Optimization. CoRR Christopher Liao, Theodoros Tsiligkaridis, Brian Kulis
2021	J	`jnl`	$β$-Annealed Variational Autoencoder for glitches. CoRR Sivaramakrishnan Sankarapandian, Brian Kulis
2021	—	`conf`	Convolutional Neural Network Denoising of Focused Ion Beam Micrographs. MLSP Minxu Peng, Mertcan Cokbas, Unay Dorken Gallastegi, Prakash Ishwar, Janusz Konrad, Brian Kulis, Vivek K. Goyal
2021	J	`jnl`	Faster Convex Lipschitz Regression via 2-block ADMM. CoRR Ali Siahkamari, Durmus Alp Emre Acar, Christopher Liao, Kelly Geyer, Venkatesh Saligrama, Brian Kulis
2021	A	`conf`	Real-time Localized Photorealistic Video Style Transfer. WACV Xide Xia, Tianfan Xue, Wei-Sheng Lai, Zheng Sun, Abby Chang, Brian Kulis, Jiawen Chen
2021	J	`jnl`	Substitutional Neural Image Compression. CoRR Xiao Wang, Wei Jiang, Wei Wang, Shan Liu, Brian Kulis, Peter Chin
2021	J	`jnl`	Tiny-CRNN: Streaming Wakeword Detection In A Low Footprint Setting. CoRR Mohammad Omar Khursheed, Christin Jose, Rajath Kumar, Gengshen Fu, Brian Kulis, Santosh Kumar Cheekatmalla
2021	C	`conf`	Tiny-CRNN: Streaming Wakeword Detection in a Low Footprint Setting. ASRU Mohammad Omar Khursheed, Christin Jose, Rajath Kumar, Gengshen Fu, Brian Kulis, Santosh Kumar Cheekatmalla
2020	A	`conf`	An Audio-Based Wakeword-Independent Verification System. INTERSPEECH Joe Wang, Rajath Kumar, Mike Rodehorst, Brian Kulis, Shiv Naga Prasad Vitaladevuni
2020	A	`conf`	Building a Robust Word-Level Wakeword Verification Network. INTERSPEECH Rajath Kumar, Mike Rodehorst, Joe Wang, Jiacheng Gu, Brian Kulis
2020	A*	`conf`	Deep Divergence Learning. ICML Hatice Kubra Cilingir, Rachel Manzelli, Brian Kulis
2020	J	`jnl`	Deep Divergence Learning. CoRR Kubra Cilingir, Rachel Manzelli, Brian Kulis
2020	—	`conf`	Joint Bilateral Learning for Real-Time Universal Photorealistic Style Transfer. ECCV (8) Xide Xia, Meng Zhang, Tianfan Xue, Zheng Sun, Hui Fang, Brian Kulis, Jiawen Chen
2020	J	`jnl`	Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer. CoRR Xide Xia, Meng Zhang, Tianfan Xue, Zheng Sun, Hui Fang, Brian Kulis, Jiawen Chen
2020	A*	`conf`	Learning to Approximate a Bregman Divergence. NeurIPS Ali Siahkamari, Xide Xia, Venkatesh Saligrama, David A. Castañón, Brian Kulis
2020	A	`conf`	Metadata-Aware End-to-End Keyword Spotting. INTERSPEECH Hongyi Liu, Apurva Abhyankar, Yuriy Mishchenko, Thibaud Sénéchal, Gengshen Fu, Brian Kulis, Noah D. Stein, Anish Shah, Shiv Naga Prasad Vitaladevuni
2020	A*	`conf`	Piecewise Linear Regression via a Difference of Convex Functions. ICML Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama
2020	J	`jnl`	Piecewise Linear Regression via a Difference of Convex Functions. CoRR Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama
2020	J	`jnl`	Real-time Localized Photorealistic Video Style Transfer. CoRR Xide Xia, Tianfan Xue, Wei-Sheng Lai, Zheng Sun, Abby Chang, Brian Kulis, Jiawen Chen
2019	A*	`conf`	Deep Metric Learning to Rank. CVPR Fatih Çakir, Kun He, Xide Xia, Brian Kulis, Stan Sclaroff
2019	J	`jnl`	Dynamic Clustering Algorithms via Small-Variance Analysis of Markov Chain Mixture Models. IEEE Trans. Pattern Anal. Mach. Intell. Trevor Campbell, Brian Kulis, Jonathan P. How
2019	J	`jnl`	Learning Bregman Divergences. CoRR Ali Siahkamari, Venkatesh Saligrama, David Castanon, Brian Kulis
2019	A*	`conf`	Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses. IJCAI Xiao Wang, Siyue Wang, Pin-Yu Chen, Yanzhi Wang, Brian Kulis, Xue Lin, Sang Chin
2019	J	`jnl`	Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses. CoRR Xiao Wang, Siyue Wang, Pin-Yu Chen, Yanzhi Wang, Brian Kulis, Xue Lin, Peter Chin
2018	—	`conf`	Conditioning Deep Generative Raw Audio Models for Structured Automatic Music. ISMIR Rachel Manzelli, Vijay Thakkar, Ali Siahkamari, Brian Kulis
2018	J	`jnl`	Conditioning Deep Generative Raw Audio Models for Structured Automatic Music. CoRR Rachel Manzelli, Vijay Thakkar, Ali Siahkamari, Brian Kulis
2018	J	`jnl`	Inferring Human Traits From Facebook Statuses. CoRR Andrew Cutler, Brian Kulis
2018	—	`conf`	Inferring Human Traits from Facebook Statuses. SocInfo (1) Andrew Cutler, Brian Kulis
2018	—	`conf`	Stable Distribution Alignment Using the Dual of the Adversarial Distance. ICLR (Workshop) Ben Usman, Kate Saenko, Brian Kulis
2017	A	`conf`	Combinatorial Topic Models using Small-Variance Asymptotics. AISTATS Ke Jiang, Suvrit Sra, Brian Kulis
2017	J	`jnl`	Stable Distribution Alignment Using the Dual of the Adversarial Distance. CoRR Ben Usman, Kate Saenko, Brian Kulis
2017	J	`jnl`	W-Net: A Deep Model for Fully Unsupervised Image Segmentation. CoRR Xide Xia, Brian Kulis
2016	J	`jnl`	A Sufficient Statistics Construction of Bayesian Nonparametric Exponential Family Conjugate Models. CoRR Robert Finn, Brian Kulis
2016	J	`jnl`	Combinatorial Topic Models using Small-Variance Asymptotics. CoRR Ke Jiang, Suvrit Sra, Brian Kulis
2016	A*	`conf`	Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics. ICML Anirban Roychowdhury, Brian Kulis, Srinivasan Parthasarathy
2015	A	`conf`	A Sufficient Statistics Construction of Exponential Family Levy Measure Densities for Nonparametric Conjugate Models. AISTATS Robert Finn, Brian Kulis
2015	A	`conf`	Gamma Processes, Stick-Breaking, and Variational Inference. AISTATS Anirban Roychowdhury, Brian Kulis
2015	A	`conf`	Power-Law Graph Cuts. AISTATS Xiangyang Zhou, Jiaxin Zhang, Brian Kulis
2015	A*	`conf`	Revisiting kernelized locality-sensitive hashing for improved large-scale image retrieval. CVPR Ke Jiang, Qichao Que, Brian Kulis
2014	J	`jnl`	Asymmetric and Category Invariant Feature Transformations for Domain Adaptation. Int. J. Comput. Vis. Judy Hoffman, Erik Rodner, Jeff Donahue, Brian Kulis, Kate Saenko
2014	J	`jnl`	Gamma Processes, Stick-Breaking, and Variational Inference. CoRR Anirban Roychowdhury, Brian Kulis
2014	J	`jnl`	Power-Law Graph Cuts. CoRR Xiangyang Zhou, Jiaxin Zhang, Brian Kulis
2014	J	`jnl`	Revisiting Kernelized Locality-Sensitive Hashing for Improved Large-Scale Image Retrieval. CoRR Ke Jiang, Qichao Que, Brian Kulis
2013	J	`jnl`	Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture CoRR Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How
2013	—	`conf`	Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture. NIPS Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How, Lawrence Carin
2013	—	`conf`	MAD-Bayes: MAP-based Asymptotic Derivations from Bayes. ICML (3) Tamara Broderick, Brian Kulis, Michael I. Jordan
2013	J	`jnl`	Metric Learning: A Survey. Found. Trends Mach. Learn. Brian Kulis
2013	—	`conf`	Small-Variance Asymptotics for Hidden Markov Models. NIPS Anirban Roychowdhury, Ke Jiang, Brian Kulis
2012	—	`conf`	Discovering Latent Domains for Multisource Domain Adaptation. ECCV (2) Judy Hoffman, Brian Kulis, Trevor Darrell, Kate Saenko
2012	J	`jnl`	Kernelized Locality-Sensitive Hashing. IEEE Trans. Pattern Anal. Mach. Intell. Brian Kulis, Kristen Grauman
2012	J	`jnl`	Metric and Kernel Learning Using a Linear Transformation. J. Mach. Learn. Res. Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon
2012	A*	`conf`	Revisiting k-means: New Algorithms via Bayesian Nonparametrics. ICML Brian Kulis, Michael I. Jordan
2012	—	`conf`	Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models. NIPS Ke Jiang, Brian Kulis, Michael I. Jordan
2011	A	`conf`	Metric learning for reinforcement learning agents. AAMAS Matthew E. Taylor, Brian Kulis, Fei Sha
2011	J	`jnl`	Revisiting k-means: New Algorithms via Bayesian Nonparametrics CoRR Brian Kulis, Michael I. Jordan
2011	A*	`conf`	What you saw is not what you get: Domain adaptation using asymmetric kernel transforms. CVPR Brian Kulis, Kate Saenko, Trevor Darrell
2010	—	`conf`	Adapting Visual Category Models to New Domains. ECCV (4) Kate Saenko, Brian Kulis, Mario Fritz, Trevor Darrell
2010	A*	`conf`	Implicit Online Learning. ICML Brian Kulis, Peter L. Bartlett
2010	—	`conf`	Inductive Regularized Learning of Kernel Functions. NIPS Prateek Jain, Brian Kulis, Inderjit S. Dhillon
2009	A	`conf`	Convex Perturbations for Scalable Semidefinite Programming. AISTATS Brian Kulis, Suvrit Sra, Inderjit S. Dhillon
2009	J	`jnl`	Fast Similarity Search for Learned Metrics. IEEE Trans. Pattern Anal. Mach. Intell. Brian Kulis, Prateek Jain, Kristen Grauman
2009	A*	`conf`	Kernelized locality-sensitive hashing for scalable image search. ICCV Brian Kulis, Kristen Grauman
2009	—	`conf`	Learning to Hash with Binary Reconstructive Embeddings. NIPS Brian Kulis, Trevor Darrell
2009	J	`jnl`	Low-Rank Kernel Learning with Bregman Matrix Divergences. J. Mach. Learn. Res. Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
2009	J	`jnl`	Metric and Kernel Learning using a Linear Transformation. CoRR Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon
2009	J	`jnl`	Semi-supervised graph clustering: a kernel approach. Mach. Learn. Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney
2008	A*	`conf`	Fast image search for learned metrics. CVPR Prateek Jain, Brian Kulis, Kristen Grauman
2008	—	`conf`	Online Metric Learning and Fast Similarity Search. NIPS Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman
2007	A	`conf`	Fast Low-Rank Semidefinite Programming for Embedding and Clustering. AISTATS Brian Kulis, Arun C. Surendran, John C. Platt
2007	A*	`conf`	Information-theoretic metric learning. ICML Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon
2007	J	`jnl`	Weighted Graph Cuts without Eigenvectors A Multilevel Approach. IEEE Trans. Pattern Anal. Mach. Intell. Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
2006	A*	`conf`	Learning low-rank kernel matrices. ICML Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
2005	A*	`conf`	A fast kernel-based multilevel algorithm for graph clustering. KDD Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
2005	A*	`conf`	Semi-supervised graph clustering: a kernel approach. ICML Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney
2004	A*	`conf`	Kernel k-means: spectral clustering and normalized cuts. KDD Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
2003	A*	`conf`	Natural communities in large linked networks. KDD John E. Hopcroft, Omar Khan, Brian Kulis, Bart Selman