Michael Maire

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 61

Top Topics

Contour Detection

Visual Representation

Top Venues

Publications

Xiao Zhang, William Gao, Seemandhar Jain, Michael Maire, David A. Forsyth, Anand Bhattad
Latent Intrinsics Emerge from Training to Relight. CoRR (2024)
Xin Yuan, Rana Hanocka, Michael Maire
Generative Lifting of Multiview to 3D from Unknown Pose: Wrapping NeRF inside Diffusion. CoRR (2024)
Mingyuan Xiang, Xuhan Xie, Pedro Savarese, Xin Yuan, Michael Maire, Yanjing Li
Drop-Connect as a Fault-Tolerance Approach for RRAM-based Deep Neural Network Accelerators. VTS (2024)
Mingyuan Xiang, Xuhan Xie, Pedro Savarese, Xin Yuan, Michael Maire, Yanjing Li
Drop-Connect as a Fault-Tolerance Approach for RRAM-based Deep Neural Network Accelerators. CoRR (2024)
Xiao Zhang, Ruoxi Jiang, William Gao, Rebecca Willett, Michael Maire
Residual Connections Harm Self-Supervised Abstract Feature Learning. CoRR (2024)
Yuhan Liu, Chengcheng Wan, Kuntai Du, Henry Hoffmann, Junchen Jiang, Shan Lu, Michael Maire
ChameleonAPI: Automatic and Efficient Customization of Neural Networks for ML Applications. OSDI (2024)
Yuhan Liu, Hanchen Li, Yihua Cheng, Siddhant Ray, Yuyang Huang, Qizheng Zhang, Kuntai Du, Jiayi Yao, Shan Lu, Ganesh Ananthanarayanan, Michael Maire, Henry Hoffmann, Ari Holtzman, Junchen Jiang
CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Serving. SIGCOMM (2024)
Chengcheng Wan, Yuhan Liu, Kuntai Du, Henry Hoffmann, Junchen Jiang, Michael Maire, Shan Lu
Run-Time Prevention of Software Integration Failures of Machine Learning APIs. Proc. ACM Program. Lang. 7 (OOPSLA2) (2023)
Xin Yuan, Michael Maire
Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation. CoRR (2023)
Xiao Zhang, David Yunis, Michael Maire
Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations. CoRR (2023)
Xin Yuan, Pedro Savarese, Michael Maire
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation. CoRR (2023)
Zhuokai Zhao, Takumi Matsuzawa, William Irvine, Michael Maire, Gordon L. Kindlmann
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits. CoRR (2023)
Xiao Zhang, Michael Maire
Structural Adversarial Objectives for Self-Supervised Representation Learning. CoRR (2023)
Cyrus Zhou, Vaughn Richard, Pedro Savarese, Zachary Hassman, Michael Maire, Michael DiBrino, Yanjing Li
SySMOL: A Hardware-software Co-design Framework for Ultra-Low and Fine-Grained Mixed-Precision Neural Networks. CoRR (2023)
Yuhan Liu, Hanchen Li, Kuntai Du, Jiayi Yao, Yihua Cheng, Yuyang Huang, Shan Lu, Michael Maire, Henry Hoffmann, Ari Holtzman, Ganesh Ananthanarayanan, Junchen Jiang
CacheGen: Fast Context Loading for Language Model Applications. CoRR (2023)
Yuhan Liu, Chengcheng Wan, Kuntai Du, Henry Hoffmann, Junchen Jiang, Shan Lu, Michael Maire
Automatic and Efficient Customization of Neural Networks for ML Applications. CoRR (2023)
Sudarshan Babu, Richard Liu, Avery Zhou, Michael Maire, Greg Shakhnarovich, Rana Hanocka
HyperFields: Towards Zero-Shot Generation of NeRFs from Text. CoRR (2023)
Xin Yuan, Pedro Savarese, Michael Maire
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation. NeurIPS (2023)
Tri Huynh, Simon Kornblith, Matthew R. Walter, Michael Maire, Maryam Khademi
Boosting Contrastive Self-Supervised Learning with False Negative Cancellation. WACV (2022)
Pedro Savarese, Xin Yuan, Yanjing Li, Michael Maire
Not All Bits have Equal Value: Heterogeneous Precisions via Trainable Noise. NeurIPS (2022)
Chengcheng Wan, Shicheng Liu, Sophie Xie, Yifan Liu, Henry Hoffmann, Michael Maire, Shan Lu
Automated Testing of Software that Uses Machine Learning APIs. ICSE (2022)
Pedro Savarese, Sunnie S. Y. Kim, Michael Maire, Greg Shakhnarovich, David McAllester
Information-Theoretic Segmentation by Inpainting Error Maximization. CVPR (2021)
Pedro Savarese, David McAllester, Sudarshan Babu, Michael Maire
Domain-Independent Dominance of Adaptive Methods. CVPR (2021)
Chengcheng Wan, Shicheng Liu, Henry Hoffmann, Michael Maire, Shan Lu
Are Machine Learning Cloud APIs Used Correctly? ICSE (2021)
Xin Yuan, Pedro Henrique Pamplona Savarese, Michael Maire
Growing Efficient Deep Networks by Structured Continuous Sparsification. ICLR (2021)
Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, Yilin Wang, Michael Maire, Ajinkya Kale, Baldo Faieta
Multimodal Contrastive Training for Visual Representation Learning. CVPR (2021)
Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, Yilin Wang, Michael Maire, Ajinkya Kale, Baldo Faieta
Multimodal Contrastive Training for Visual Representation Learning. CoRR (2021)
Sudarshan Babu, Pedro Savarese, Michael Maire
Meta-Learning via Learning with Distributed Memory. NeurIPS (2021)
Chengcheng Wan, Shicheng Liu, Henry Hoffmann, Michael Maire, Shan Lu
A Replication of Are Machine Learning Cloud APIs Used Correctly. ICSE (Companion Volume) (2021)
Chengcheng Wan, Henry Hoffmann, Shan Lu, Michael Maire
Orthogonalized SGD and Nested Architectures for Anytime Neural Networks. ICML (2020)
Tri Huynh, Michael Maire, Matthew R. Walter
Multigrid Neural Memory. ICML (2020)
Chengcheng Wan, Henry Hoffmann, Shan Lu, Michael Maire
Orthogonalized SGD and Nested Architectures for Anytime Neural Networks. CoRR (2020)
Xiao Zhang, Michael Maire
Self-Supervised Visual Representation Learning from Hierarchical Grouping. NeurIPS (2020)
Pedro Savarese, Sunnie S. Y. Kim, Michael Maire, Greg Shakhnarovich, David McAllester
Information-Theoretic Segmentation by Inpainting Error Maximization. CoRR (2020)
Xin Yuan, Pedro Savarese, Michael Maire
Growing Efficient Deep Networks by Structured Continuous Sparsification. CoRR (2020)
Chengcheng Wan, Muhammad Husni Santriaji, Eri Rogers, Henry Hoffmann, Michael Maire, Shan Lu
ALERT: Accurate Learning for Energy and Timeliness. USENIX Annual Technical Conference (2020)
Pedro Savarese, Hugo Silva, Michael Maire
Winning the Lottery with Continuous Sparsification. NeurIPS (2020)
Tri Huynh, Simon Kornblith, Matthew R. Walter, Michael Maire, Maryam Khademi
Boosting Contrastive Self-Supervised Learning with False Negative Cancellation. CoRR (2020)
Xiao Zhang, Michael Maire
Self-Supervised Visual Representation Learning from Hierarchical Grouping. CoRR (2020)
Haochen Wang, Ruotian Luo, Michael Maire, Greg Shakhnarovich
Pixel Consensus Voting for Panoptic Segmentation. CoRR (2020)
Haochen Wang, Ruotian Luo, Michael Maire, Greg Shakhnarovich
Pixel Consensus Voting for Panoptic Segmentation. CVPR (2020)
Chengcheng Wan, Muhammad Husni Santriaji, Eri Rogers, Henry Hoffmann, Michael Maire, Shan Lu
ALERT: Accurate Anytime Learning for Energy and Timeliness. CoRR (2019)
Pedro Savarese, Michael Maire
Learning Implicitly Recurrent CNNs Through Parameter Sharing. CoRR (2019)
Pedro Savarese, David McAllester, Sudarshan Babu, Michael Maire
Domain-independent Dominance of Adaptive Methods. CoRR (2019)
Pedro Savarese, Hugo Silva, Michael Maire
Winning the Lottery with Continuous Sparsification. CoRR (2019)
Pedro Savarese, Michael Maire
Learning Implicitly Recurrent CNNs Through Parameter Sharing. ICLR (Poster) (2019)
Tri Huynh, Michael Maire, Matthew R. Walter
Multigrid Neural Memory. CoRR (2019)
Mohammadreza Mostajabi, Michael Maire, Gregory Shakhnarovich
Regularizing Deep Networks by Modeling and Predicting Label Structure. CVPR (2018)
Huaizu Jiang, Gustav Larsson, Michael Maire, Greg Shakhnarovich, Erik G. Learned-Miller
Self-Supervised Relative Depth Learning for Urban Scene Understanding. ECCV (11) (2018)
Ligeng Zhu, Ruizhi Deng, Michael Maire, Zhiwei Deng, Greg Mori, Ping Tan
Sparsely Aggregated Convolutional Networks. ECCV (12) (2018)
Mohammadreza Mostajabi, Michael Maire, Gregory Shakhnarovich
Regularizing Deep Networks by Modeling and Predicting Label Structure. CoRR (2018)
Huaizu Jiang, Erik G. Learned-Miller, Gustav Larsson, Michael Maire, Greg Shakhnarovich
Self-Supervised Depth Learning for Urban Scene Understanding. CoRR (2017)
Gustav Larsson, Michael Maire, Gregory Shakhnarovich
Colorization as a Proxy Task for Visual Understanding. CVPR (2017)
Tsung-Wei Ke, Michael Maire, Stella X. Yu
Multigrid Neural Architectures. CVPR (2017)
Gustav Larsson, Michael Maire, Gregory Shakhnarovich
FractalNet: Ultra-Deep Neural Networks without Residuals. ICLR (Poster) (2017)
Gustav Larsson, Michael Maire, Gregory Shakhnarovich
Colorization as a Proxy Task for Visual Understanding. CoRR (2017)
Gustav Larsson, Michael Maire, Gregory Shakhnarovich
Learning Representations for Automatic Colorization. CoRR (2016)
Tsung-Wei Ke, Michael Maire, Stella X. Yu
Neural Multigrid. CoRR (2016)
Michael Maire, Takuya Narihira, Stella X. Yu
Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embedding. CVPR (2016)
Gustav Larsson, Michael Maire, Gregory Shakhnarovich
FractalNet: Ultra-Deep Neural Networks without Residuals. CoRR (2016)
Gustav Larsson, Michael Maire, Gregory Shakhnarovich
Learning Representations for Automatic Colorization. ECCV (4) (2016)
Michael Maire, Takuya Narihira, Stella X. Yu
Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embedding. CoRR (2015)
Takuya Narihira, Michael Maire, Stella X. Yu
Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression. ICCV (2015)
Takuya Narihira, Michael Maire, Stella X. Yu
Learning lightness from human judgement on relative reflectance. CVPR (2015)
Takuya Narihira, Michael Maire, Stella X. Yu
Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression. CoRR (2015)
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, C. Lawrence Zitnick
Microsoft COCO: Common Objects in Context. ECCV (5) (2014)
Michael Maire, Stella X. Yu, Pietro Perona
Reconstructive Sparse Code Transfer for Contour Detection and Semantic Labeling. CoRR (2014)
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, Lubomir D. Bourdev, Ross B. Girshick, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, C. Lawrence Zitnick
Microsoft COCO: Common Objects in Context. CoRR (2014)
Michael Maire, Stella X. Yu, Pietro Perona
Reconstructive Sparse Code Transfer for Contour Detection and Semantic Labeling. ACCV (4) (2014)
Michael Maire, Stella X. Yu
Progressive Multigrid Eigensolvers for Multiscale Spectral Segmentation. ICCV (2013)
Michael Maire, Stella X. Yu, Pietro Perona
Hierarchical Scene Annotation. BMVC (2013)
Michael Maire, Stella X. Yu, Pietro Perona
Object detection and segmentation from joint embedding of parts and pixels. ICCV (2011)
Pablo Arbelaez, Michael Maire, Charless C. Fowlkes, Jitendra Malik
Contour Detection and Hierarchical Image Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 33 (5) (2011)
Patrik Sundberg, Thomas Brox, Michael Maire, Pablo Arbelaez, Jitendra Malik
Occlusion boundary detection and figure/ground assignment from optical flow. CVPR (2011)
Michael Maire
Simultaneous Segmentation and Figure/Ground Organization Using Angular Embedding. ECCV (2) (2010)
Pablo Arbelaez, Michael Maire, Charless C. Fowlkes, Jitendra Malik
From contours to regions: An empirical evaluation. CVPR (2009)
Michael Maire, Pablo Arbelaez, Charless C. Fowlkes, Jitendra Malik
Using contours to detect and localize junctions in natural images. CVPR (2008)
Hao Zhang, Alexander C. Berg, Michael Maire, Jitendra Malik
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition. CVPR (2) (2006)
Jaety Edwards, Yee Whye Teh, David A. Forsyth, Roger Bock, Michael Maire, Grace Vesom
Making Latin Manuscripts Searchable using gHMMs. NIPS (2004)
Pierre Moreels, Michael Maire, Pietro Perona
Recognition by Probabilistic Hypothesis Construction. ECCV (1) (2004)
Tamara L. Berg, Alexander C. Berg, Jaety Edwards, Michael Maire, Ryan White, Yee Whye Teh, Erik G. Learned-Miller, David A. Forsyth
Names and Faces in the News. CVPR (2) (2004)