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2020 – today
- 2024
[j2]Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind:
The Slingshot Effect: A Late-Stage Optimization Anomaly in Adaptive Gradient Methods. Trans. Mach. Learn. Res. 2024 (2024)- [c31]Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, Josh M. Susskind:
Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images. 3DV 2024: 685-696 - [c30]Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Joshua M. Susskind, Shuangfei Zhai:
Generative Modeling with Phase Stochastic Bridge. ICLR 2024 - [c29]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly:
Matryoshka Diffusion Models. ICLR 2024 - [c28]Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Vaishaal Shankar, Alexander T. Toshev, Joshua M. Susskind, Armand Joulin:
Scalable Pre-training of Large Autoregressive Image Models. ICML 2024 - [c27]Jiatao Gu, Chen Wang, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Joshua M. Susskind:
Data-free Distillation of Diffusion Models with Bootstrapping. ICML 2024 - [i42]Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Alexander Toshev, Vaishaal Shankar, Joshua M. Susskind, Armand Joulin:
Scalable Pre-training of Large Autoregressive Image Models. CoRR abs/2401.08541 (2024) - [i41]Yizhe Zhang, He Bai, Ruixiang Zhang, Jiatao Gu, Shuangfei Zhai, Josh M. Susskind, Navdeep Jaitly:
How Far Are We from Intelligent Visual Deductive Reasoning? CoRR abs/2403.04732 (2024) - [i40]Ying Shen, Yizhe Zhang, Shuangfei Zhai, Lifu Huang, Joshua M. Susskind, Jiatao Gu:
Many-to-many Image Generation with Auto-regressive Diffusion Models. CoRR abs/2404.03109 (2024) - [i39]Jiatao Gu, Ying Shen, Shuangfei Zhai, Yizhe Zhang, Navdeep Jaitly, Joshua M. Susskind:
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling. CoRR abs/2405.21048 (2024) - [i38]Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Josh M. Susskind, Navdeep Jaitly, Shuangfei Zhai:
Improving GFlowNets for Text-to-Image Diffusion Alignment. CoRR abs/2406.00633 (2024) - [i37]Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Josh M. Susskind, Shuangfei Zhai:
DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation. CoRR abs/2410.08159 (2024) - 2023
- [c26]Ziwen Chen, Kaushik Patnaik, Shuangfei Zhai, Alvin Wan, Zhile Ren, Alexander G. Schwing, Alex Colburn, Fuxin Li:
AutoFocusFormer: Image Segmentation off the Grid. CVPR 2023: 18227-18236 - [c25]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, Joshua M. Susskind:
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation. ICLR 2023 - [c24]Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind:
Stabilizing Transformer Training by Preventing Attention Entropy Collapse. ICML 2023: 40770-40803 - [c23]Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Joshua M. Susskind, Navdeep Jaitly:
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model. NeurIPS 2023 - [i36]David Berthelot, Arnaud Autef, Jierui Lin, Dian Ang Yap, Shuangfei Zhai, Siyuan Hu, Daniel Zheng, Walter Talbott, Eric Gu:
TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation. CoRR abs/2303.04248 (2023) - [i35]Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind:
Stabilizing Transformer Training by Preventing Attention Entropy Collapse. CoRR abs/2303.06296 (2023) - [i34]Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, Josh M. Susskind:
Learning Controllable 3D Diffusion Models from Single-view Images. CoRR abs/2304.06700 (2023) - [i33]Ziwen Chen, Kaushik Patnaik, Shuangfei Zhai, Alvin Wan, Zhile Ren, Alexander G. Schwing, Alex Colburn, Fuxin Li:
AutoFocusFormer: Image Segmentation off the Grid. CoRR abs/2304.12406 (2023) - [i32]Yizhe Zhang, Jiatao Gu, Zhuofeng Wu
, Shuangfei Zhai, Josh M. Susskind, Navdeep Jaitly:
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model. CoRR abs/2306.02531 (2023) - [i31]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Josh M. Susskind:
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping. CoRR abs/2306.05544 (2023) - [i30]Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Josh M. Susskind, Shuangfei Zhai:
Generative Modeling with Phase Stochastic Bridges. CoRR abs/2310.07805 (2023) - [i29]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Josh M. Susskind, Navdeep Jaitly:
Matryoshka Diffusion Models. CoRR abs/2310.15111 (2023) - 2022
- [c22]Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind:
Learning Representation from Neural Fisher Kernel with Low-rank Approximation. ICLR 2022 - [c21]Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Y. Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M. Susskind:
Position Prediction as an Effective Pretraining Strategy. ICML 2022: 26010-26027 - [c20]Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Joshua M. Susskind:
Regularized Training of Nearest Neighbor Language Models. NAACL-HLT (Student Research Workshop) 2022: 25-30 - [c19]Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua M. Susskind:
GAUDI: A Neural Architect for Immersive 3D Scene Generation. NeurIPS 2022 - [i28]Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Josh M. Susskind:
Learning Representation from Neural Fisher Kernel with Low-rank Approximation. CoRR abs/2202.01944 (2022) - [i27]Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind:
The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon. CoRR abs/2206.04817 (2022) - [i26]Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Yitan Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M. Susskind:
Position Prediction as an Effective Pretraining Strategy. CoRR abs/2207.07611 (2022) - [i25]Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Josh M. Susskind:
GAUDI: A Neural Architect for Immersive 3D Scene Generation. CoRR abs/2207.13751 (2022) - [i24]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, Josh M. Susskind:
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation. CoRR abs/2210.04955 (2022) - 2021
- [c18]Chen Huang, Shuangfei Zhai, Pengsheng Guo, Josh M. Susskind:
MetricOpt: Learning To Optimize Black-Box Evaluation Metrics. CVPR 2021: 174-183 - [c17]Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh:
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. ICML 2021: 11319-11328 - [c16]Miguel Ángel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind:
On the generalization of learning-based 3D reconstruction. WACV 2021: 2179-2188 - [i23]Chen Huang, Shuangfei Zhai, Pengsheng Guo, Josh M. Susskind:
MetricOpt: Learning to Optimize Black-Box Evaluation Metrics. CoRR abs/2104.10631 (2021) - [i22]Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh:
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. CoRR abs/2105.08140 (2021) - [i21]Shuangfei Zhai, Walter Talbott, Nitish Srivastava, Chen Huang, Hanlin Goh, Ruixiang Zhang, Josh M. Susskind:
An Attention Free Transformer. CoRR abs/2105.14103 (2021) - [i20]Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang:
Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks. CoRR abs/2107.00364 (2021) - [i19]Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Josh M. Susskind:
Regularized Training of Nearest Neighbor Language Models. CoRR abs/2109.08249 (2021) - [i18]Nitish Srivastava, Walter Talbott, Martin Bertran Lopez, Shuangfei Zhai, Josh M. Susskind:
Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models. CoRR abs/2112.01163 (2021) - 2020
- [c15]Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan:
Collegial Ensembles. NeurIPS 2020 - [i17]Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan:
Collegial Ensembles. CoRR abs/2006.07678 (2020) - [i16]Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Carlos Guestrin, Josh M. Susskind:
Set Distribution Networks: a Generative Model for Sets of Images. CoRR abs/2006.10705 (2020) - [i15]Miguel Ángel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind:
On the generalization of learning-based 3D reconstruction. CoRR abs/2006.15427 (2020)
2010 – 2019
- 2019
- [c14]Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind:
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. ICML 2019: 2891-2900 - [c13]Shichao Liu, Shuangfei Zhai, Lida Zhu, Fuxi Zhu, Zhongfei (Mark) Zhang, Wen Zhang:
Efficient Network Representations Learning: An Edge-Centric Perspective. KSEM (2) 2019: 373-388 - [c12]Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind:
Adversarial Fisher Vectors for Unsupervised Representation Learning. NeurIPS 2019: 11156-11166 - [i14]Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind:
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. CoRR abs/1905.05895 (2019) - [i13]Alaaeldin El-Nouby, Shuangfei Zhai, Graham W. Taylor, Joshua M. Susskind:
Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking. CoRR abs/1910.12770 (2019) - [i12]Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind:
Adversarial Fisher Vectors for Unsupervised Representation Learning. CoRR abs/1910.13101 (2019) - 2018
- [c11]Zheng Zhang, Shuangfei Zhai, Lijun Yin:
Identity-based Adversarial Training of Deep CNNs for Facial Action Unit Recognition. BMVC 2018: 226 - 2017
- [c10]Nana Li, Shuangfei Zhai, Zhongfei Zhang, Boying Liu:
Structural Correspondence Learning for Cross-Lingual Sentiment Classification with One-to-Many Mappings. AAAI 2017: 3490-3496 - [c9]Yongxi Lu, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, Rogério Schmidt Feris:
Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification. CVPR 2017: 1131-1140 - [c8]Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogério Schmidt Feris:
S3Pool: Pooling with Stochastic Spatial Sampling. CVPR 2017: 4003-4011 - [c7]Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, Yan Liu:
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records. ICDM 2017: 787-792 - [i11]Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, Yan Liu:
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records. CoRR abs/1709.01648 (2017) - [i10]Chen Zheng, Shuangfei Zhai, Zhongfei Zhang:
A Deep Learning Approach for Expert Identification in Question Answering Communities. CoRR abs/1711.05350 (2017) - 2016
- [j1]Peng Xia, Shuangfei Zhai, Benyuan Liu, Yizhou Sun, Cindy X. Chen:
Design of reciprocal recommendation systems for online dating. Soc. Netw. Anal. Min. 6(1): 32:1-32:16 (2016) - [c6]Shuangfei Zhai, Zhongfei (Mark) Zhang:
Semisupervised Autoencoder for Sentiment Analysis. AAAI 2016: 1394-1400 - [c5]Shuangfei Zhai, Yu Cheng, Weining Lu, Zhongfei Zhang:
Deep Structured Energy Based Models for Anomaly Detection. ICML 2016: 1100-1109 - [c4]Shuangfei Zhai, Keng-hao Chang, Ruofei Zhang, Zhongfei (Mark) Zhang:
DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks. KDD 2016: 1295-1304 - [c3]Shuangfei Zhai, Yu Cheng, Zhongfei (Mark) Zhang, Weining Lu:
Doubly Convolutional Neural Networks. NIPS 2016: 1082-1090 - [c2]Shuangfei Zhai, Keng-hao Chang, Ruofei Zhang, Zhongfei Zhang:
Attention Based Recurrent Neural Networks for Online Advertising. WWW (Companion Volume) 2016: 141-142 - [i9]Shuangfei Zhai, Yu Cheng, Weining Lu, Zhongfei Zhang:
Deep Structured Energy Based Models for Anomaly Detection. CoRR abs/1605.07717 (2016) - [i8]Shuangfei Zhai, Yu Cheng, Weining Lu, Zhongfei Zhang:
Doubly Convolutional Neural Networks. CoRR abs/1610.09716 (2016) - [i7]Shuangfei Zhai, Yu Cheng, Rogério Schmidt Feris, Zhongfei Zhang:
Generative Adversarial Networks as Variational Training of Energy Based Models. CoRR abs/1611.01799 (2016) - [i6]Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogério Schmidt Feris:
S3Pool: Pooling with Stochastic Spatial Sampling. CoRR abs/1611.05138 (2016) - [i5]Yongxi Lu, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, Rogério Schmidt Feris:
Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification. CoRR abs/1611.05377 (2016) - [i4]Nana Li, Shuangfei Zhai, Zhongfei Zhang, Boying Liu:
Structural Correspondence Learning for Cross-lingual Sentiment Classification with One-to-many Mappings. CoRR abs/1611.08737 (2016) - 2015
- [c1]Shuangfei Zhai, Zhongfei (Mark) Zhang:
Dropout Training of Matrix Factorization and Autoencoder for Link Prediction in Sparse Graphs. SDM 2015: 451-459 - [i3]Shuangfei Zhai, Zhongfei Zhang:
Manifold Regularized Discriminative Neural Networks. CoRR abs/1511.06328 (2015) - [i2]Shuangfei Zhai, Zhongfei Zhang:
Semisupervised Autoencoder for Sentiment Analysis. CoRR abs/1512.04466 (2015) - [i1]Shuangfei Zhai, Zhongfei Zhang:
Dropout Training of Matrix Factorization and Autoencoder for Link Prediction in Sparse Graphs. CoRR abs/1512.04483 (2015)
Coauthor Index
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last updated on 2024-11-19 20:47 CET by the dblp team
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