Instance-level Semisupervised Multiple Instance Learning. - Yangqing Jia; Changshui Zhang (AAAI, 2008)

Trace Ratio Criterion for Feature Selection. - Feiping Nie 001; Shiming Xiang; Yangqing Jia; Changshui Zhang; Shuicheng Yan (AAAI, 2008)

Normalized tree partitioning for image segmentation. - Jingdong Wang 001; Yangqing Jia; Xian-Sheng Hua 001; Changshui Zhang; Long Quan (CVPR, 2008)

Augmented tree partitioning for interactive image segmentation. - Yangqing Jia; Jingdong Wang 001; Changshui Zhang; Xian-Sheng Hua 001 (ICIP, 2008)

Learning distance metric for semi-supervised image segmentation. - Yangqing Jia; Changshui Zhang (ICIP, 2008)

Local Regularized Least-Square Dimensionality Reduction. - Yangqing Jia; Changshui Zhang (ICPR, 2008)

Finding image exemplars using fast sparse affinity propagation. - Yangqing Jia; Jingdong Wang 001; Changshui Zhang; Xian-Sheng Hua 001 (ACM Multimedia, 2008)

Distortion-Free Nonlinear Dimensionality Reduction. - Yangqing Jia; Zheng Wang 010; Changshui Zhang (ECML/PKDD (1), 2008)

Semi-Supervised Classification on Evolutionary Data. - Yangqing Jia; Shuicheng Yan; Changshui Zhang (IJCAI, 2009)

Front-view vehicle detection by Markov chain Monte Carlo method. - Yangqing Jia; Changshui Zhang (Pattern Recognit., 2009)

Semi-supervised orthogonal discriminant analysis via label propagation. - Feiping Nie 001; Shiming Xiang; Yangqing Jia; Changshui Zhang (Pattern Recognit., 2009)

Trace Ratio Problem Revisited. - Yangqing Jia; Feiping Nie 001; Changshui Zhang (IEEE Trans. Neural Networks, 2009)

Factorized Latent Spaces with Structured Sparsity. - Yangqing Jia; Mathieu Salzmann; Trevor Darrell (NIPS, 2010)

Learning cross-modality similarity for multinomial data. - Yangqing Jia; Mathieu Salzmann; Trevor Darrell (ICCV, 2011)

A category-level 3-D object dataset: Putting the Kinect to work. - Allison Janoch; Sergey Karayev; Yangqing Jia; Jonathan T. Barron; Mario Fritz; Kate Saenko; Trevor Darrell (ICCV Workshops, 2011)

Practical 3-D object detection using category and instance-level appearance models. - Kate Saenko; Sergey Karayev; Yangqing Jia; Alex Shyr; Allison Janoch; Jonathan Long; Mario Fritz; Trevor Darrell (IROS, 2011)

Heavy-tailed Distances for Gradient Based Image Descriptors. - Yangqing Jia; Trevor Darrell (NIPS, 2011)

Beyond spatial pyramids: Receptive field learning for pooled image features. - Yangqing Jia; Chang Huang; Trevor Darrell (CVPR, 2012)

Learning with Recursive Perceptual Representations. - Oriol Vinyals; Yangqing Jia; Li Deng 001; Trevor Darrell (NIPS, 2012)

Factorized Multi-Modal Topic Model. - Seppo Virtanen; Yangqing Jia; Arto Klami; Trevor Darrell (UAI, 2012)

Latent Task Adaptation with Large-Scale Hierarchies. - Yangqing Jia; Trevor Darrell (ICCV, 2013)

Category-Independent Object-Level Saliency Detection. - Yangqing Jia; Mei Han (ICCV, 2013)

On Compact Codes for Spatially Pooled Features. - Yangqing Jia; Oriol Vinyals; Trevor Darrell (ICML (3), 2013)

Grounding spatial relations for human-robot interaction. - Sergio Guadarrama; Lorenzo Riano; Dave Golland; Daniel Göhring; Yangqing Jia; Dan Klein 001; Pieter Abbeel; Trevor Darrell (IROS, 2013)

Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies. - Yangqing Jia; Joshua T. Abbott; Joseph L. Austerweil; Thomas L. Griffiths 001; Trevor Darrell (NIPS, 2013)

Why Size Matters: Feature Coding as Nystrom Sampling - Oriol Vinyals; Yangqing Jia; Trevor Darrell (ICLR (Workshop), 2013)

Pooling-Invariant Image Feature Learning - Yangqing Jia; Oriol Vinyals; Trevor Darrell (CoRR, 2013)

A Category-Level 3D Object Dataset: Putting the Kinect to Work. - Allison Janoch; Sergey Karayev; Yangqing Jia; Jonathan T. Barron; Mario Fritz; Kate Saenko; Trevor Darrell (Consumer Depth Cameras for Computer Vision, 2013)

Large-Scale Object Classification Using Label Relation Graphs. - Jia Deng 001; Nan Ding 002; Yangqing Jia; Andrea Frome; Kevin Murphy 002; Samy Bengio; Yuan Li; Hartmut Neven; Hartwig Adam (ECCV (1), 2014)

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition. - Jeff Donahue; Yangqing Jia; Oriol Vinyals; Judy Hoffman; Ning Zhang 014; Eric Tzeng; Trevor Darrell (ICML, 2014)

Caffe: Convolutional Architecture for Fast Feature Embedding. - Yangqing Jia; Evan Shelhamer; Jeff Donahue; Sergey Karayev; Jonathan Long; Ross B. Girshick; Sergio Guadarrama; Trevor Darrell (ACM Multimedia, 2014)

Deep Convolutional Ranking for Multilabel Image Annotation. - Yunchao Gong; Yangqing Jia; Thomas Leung; Alexander Toshev; Sergey Ioffe (ICLR (Poster), 2014)

One-Shot Adaptation of Supervised Deep Convolutional Models. - Judy Hoffman; Eric Tzeng; Jeff Donahue; Yangqing Jia; Kate Saenko; Trevor Darrell (ICLR (Workshop Poster), 2014)

Regularized Tree Partitioning and Its Application to Unsupervised Image Segmentation. - Jingdong Wang 001; Huaizu Jiang; Yangqing Jia; Xian-Sheng Hua 001; Changshui Zhang; Long Quan (IEEE Trans. Image Process., 2014)

Learning Semantic Image Representations at a Large Scale. - Yangqing Jia (2014)

MatchNet: Unifying feature and metric learning for patch-based matching. - Xufeng Han; Thomas Leung; Yangqing Jia; Rahul Sukthankar; Alexander C. Berg (CVPR, 2015)

Going deeper with convolutions. - Christian Szegedy; Wei Liu 015; Yangqing Jia; Pierre Sermanet; Scott E. Reed; Dragomir Anguelov; Dumitru Erhan; Vincent Vanhoucke; Andrew Rabinovich (CVPR, 2015)

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. - Martín Abadi; Ashish Agarwal; Paul Barham 001; Eugene Brevdo; Zhifeng Chen; Craig Citro; Gregory S. Corrado; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Ian J. Goodfellow; et al. (CoRR, 2016)

Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation. - Zhicheng Yan 001; Hao Zhang 025; Yangqing Jia; Thomas M. Breuel; Yizhou Yu (CoRR, 2016)

ML computation patterns in production systems. - Yangqing Jia (TIML@ISCA, 2017)

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour. - Priya Goyal; Piotr Dollár; Ross B. Girshick; Pieter Noordhuis; Lukasz Wesolowski; Aapo Kyrola; Andrew Tulloch; Yangqing Jia; Kaiming He (CoRR, 2017)

High performance ultra-low-precision convolutions on mobile devices. - Andrew Tulloch; Yangqing Jia (CoRR, 2017)

Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective. - Kim M. Hazelwood; Sarah Bird; David M. Brooks; Soumith Chintala; Utku Diril; Dmytro Dzhulgakov; Mohamed Fawzy; Bill Jia; Yangqing Jia; Aditya Kalro; James Law; Kevin Lee; et al. (HPCA, 2018)

Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications. - Jongsoo Park; Maxim Naumov; Protonu Basu; Summer Deng; Aravind Kalaiah; Daya Shanker Khudia; James Law; Parth Malani; Andrey Malevich; Nadathur Satish; Juan Miguel Pino; Martin Schatz; et al. (CoRR, 2018)

ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation. - Xiaoliang Dai; Peizhao Zhang; Bichen Wu; Hongxu Yin; Fei Sun; Yanghan Wang; Marat Dukhan; Yunqing Hu; Yiming Wu; Yangqing Jia; Peter Vajda; Matt Uyttendaele; et al. (CVPR, 2019)

FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search. - Bichen Wu; Xiaoliang Dai; Peizhao Zhang; Yanghan Wang; Fei Sun; Yiming Wu; Yuandong Tian; Peter Vajda; Yangqing Jia; Kurt Keutzer (CVPR, 2019)

Machine Learning at Facebook: Understanding Inference at the Edge. - Carole-Jean Wu; David Brooks 001; Kevin Chen; Douglas Chen; Sy Choudhury; Marat Dukhan; Kim M. Hazelwood; Eldad Isaac; Yangqing Jia; Bill Jia; Tommer Leyvand; Hao Lu; et al. (HPCA, 2019)

Characterizing Deep Learning Training Workloads on Alibaba-PAI. - Mengdi Wang; Chen Meng; Guoping Long; Chuan Wu 001; Jun Yang 052; Wei Lin 016; Yangqing Jia (IISWC, 2019)

AntMan: Dynamic Scaling on GPU Clusters for Deep Learning. - Wencong Xiao; Shiru Ren; Yong Li 020; Yang Zhang; Pengyang Hou; Zhi Li; Yihui Feng; Wei Lin 016; Yangqing Jia (OSDI, 2020)

Fangorn: Adaptive Execution Framework for Heterogeneous Workloads on Shared Clusters. - Yingda Chen; Jiamang Wang; Yifeng Lu; Ying Han; Zhiqiang Lv; Xuebin Min; Hua Cai; Wei Zhang 012; Haochuan Fan; Chao Li 009; Tao Guan; Wei Lin 016; et al. (Proc. VLDB Endow., 2021)

DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models. - Muyang Li; Tianle Cai; Jiaxin Cao; Qinsheng Zhang; Han Cai; Junjie Bai; Yangqing Jia; Kai Li; Song Han 003 (CVPR, 2024)

DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models. - Muyang Li; Tianle Cai; Jiaxin Cao; Qinsheng Zhang; Han Cai; Junjie Bai; Yangqing Jia; Ming-Yu Liu 001; Kai Li; Song Han 003 (CoRR, 2024)