Da-Cheng Juan

Publication Activity (10 Years)

Years Active: 2007-2023
Publications (10 Years): 67

Top Topics

Text Generation

Structured Learning

Neural Architecture

Top Venues

Publications

Jiao Sun, Deqing Fu, Yushi Hu, Su Wang, Royi Rassin, Da-Cheng Juan, Dana Alon, Charles Herrmann, Sjoerd van Steenkiste, Ranjay Krishna, Cyrus Rashtchian
DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback. CoRR (2023)
Cyrus Rashtchian, Charles Herrmann, Chun-Sung Ferng, Ayan Chakrabarti, Dilip Krishnan, Deqing Sun, Da-Cheng Juan, Andrew Tomkins
Substance or Style: What Does Your Image Embedding Know? CoRR (2023)
Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Y. Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, Kelvin Guu
RARR: Researching and Revising What Language Models Say, Using Language Models. ACL (1) (2023)
Yicheng Fan, Dana Alon, Jingyue Shen, Daiyi Peng, Keshav Kumar, Yun Long, Xin Wang, Fotis Iliopoulos, Da-Cheng Juan, Erik Vee
LayerNAS: Neural Architecture Search in Polynomial Complexity. CoRR (2023)
Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Y. Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, Kelvin Guu
Attributed Text Generation via Post-hoc Research and Revision. CoRR (2022)
Yu-Jen Chen, Wei-Hsiang Shen, Hao-Wei Chung, Jing-Hao Chiu, Da-Cheng Juan, Tsung-Ying Ho, Chi-Tung Cheng, Meng-Lin Li, Tsung-Yi Ho
Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generation. CoRR (2022)
Huang-Cheng Chou, Woan-Shiuan Chien, Da-Cheng Juan, Chi-Chun Lee
"Does it Matter When I Think You Are Lying?" Improving Deception Detection by Integrating Interlocutor's Judgements in Conversations. ACL/IJCNLP (Findings) (2021)
Zheyu Yan, Da-Cheng Juan, Xiaobo Sharon Hu, Yiyu Shi
Uncertainty Modeling of Emerging Device-based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search. CoRR (2021)
Zheyu Yan, Da-Cheng Juan, Xiaobo Sharon Hu, Yiyu Shi
Uncertainty Modeling of Emerging Device based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search. ASP-DAC (2021)
Arjun Gopalan, Da-Cheng Juan, Cesar Ilharco Magalhaes, Chun-Sung Ferng, Allan Heydon, Chun-Ta Lu, Philip Pham, George Yu, Yicheng Fan, Yueqi Wang
Neural Structured Learning: Training Neural Networks with Structured Signals. WSDM (2021)
Pranjal Awasthi, George Yu, Chun-Sung Ferng, Andrew Tomkins, Da-Cheng Juan
Adversarial Robustness Across Representation Spaces. CVPR (2021)
Shuai Zhang, Yi Tay, Wenqi Jiang, Da-Cheng Juan, Ce Zhang
Switch Spaces: Learning Product Spaces with Sparse Gating. CoRR (2021)
Chun-Ta Lu, Yun Zeng, Da-Cheng Juan, Yicheng Fan, Zhe Li, Jan Dlabal, Yi-Ting Chen, Arjun Gopalan, Allan Heydon, Chun-Sung Ferng, Reah Miyara, Ariel Fuxman, Futang Peng, Zhen Li, Tom Duerig, Andrew Tomkins
CARLS: Cross-platform Asynchronous Representation Learning System. CoRR (2021)
Yi Tay, Zhe Zhao, Dara Bahri, Donald Metzler, Da-Cheng Juan
HyperGrid Transformers: Towards A Single Model for Multiple Tasks. ICLR (2021)
Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Prakash Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Donald Metzler
OmniNet: Omnidirectional Representations from Transformers. CoRR (2021)
Wei-Cheng Tseng, Wei Wei, Da-Cheng Juan, Min Sun
Meta-CPR: Generalize to Unseen Large Number of Agents with Communication Pattern Recognition Module. CoRR (2021)
Yi Tay, Dara Bahri, Donald Metzler, Da-Cheng Juan, Zhe Zhao, Che Zheng
Synthesizer: Rethinking Self-Attention for Transformer Models. ICML (2021)
Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Prakash Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Donald Metzler
OmniNet: Omnidirectional Representations from Transformers. ICML (2021)
Yi Tay, Zhe Zhao, Dara Bahri, Donald Metzler, Da-Cheng Juan
HyperGrid: Efficient Multi-Task Transformers with Grid-wise Decomposable Hyper Projections. CoRR (2020)
Yi Tay, Dara Bahri, Donald Metzler, Da-Cheng Juan, Zhe Zhao, Che Zheng
Synthesizer: Rethinking Self-Attention in Transformer Models. CoRR (2020)
Yi Tay, Dara Bahri, Liu Yang, Donald Metzler, Da-Cheng Juan
Sparse Sinkhorn Attention. ICML (2020)
An-Chieh Cheng, Chieh Hubert Lin, Da-Cheng Juan, Wei Wei, Min Sun
InstaNAS: Instance-Aware Neural Architecture Search. AAAI (2020)
Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, Christopher Ré
Low-Dimensional Hyperbolic Knowledge Graph Embeddings. CoRR (2020)
Chieh-Yang Chen, Pei-Hsin Wang, Shih-Chieh Chang, Da-Cheng Juan, Wei Wei, Jia-Yu Pan
AirConcierge: Generating Task-Oriented Dialogue via Efficient Large-Scale Knowledge Retrieval. EMNLP (Findings) (2020)
Hsin-Ping Chou, Shih-Chieh Chang, Jia-Yu Pan, Wei Wei, Da-Cheng Juan
Remix: Rebalanced Mixup. CoRR (2020)
Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, Christopher Ré
Low-Dimensional Hyperbolic Knowledge Graph Embeddings. ACL (2020)
Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, Chandan K. Reddy
Question Answering with Long Multiple-Span Answers. EMNLP (Findings) (2020)
Hsin-Ping Chou, Shih-Chieh Chang, Jia-Yu Pan, Wei Wei, Da-Cheng Juan
Remix: Rebalanced Mixup. ECCV Workshops (6) (2020)
Jia Li, Tomas Yu, Da-Cheng Juan, Arjun Gopalan, Hong Cheng, Andrew Tomkins
Graph Autoencoders with Deconvolutional Networks. CoRR (2020)
Hung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun
Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization. NeurIPS (2020)
Li-Huang Tsai, Shih-Chieh Chang, Yu-Ting Chen, Jia-Yu Pan, Wei Wei, Da-Cheng Juan
Calibrated BatchNorm: Improving Robustness Against Noisy Weights in Neural Networks. CoRR (2020)
Yi Tay, Dara Bahri, Liu Yang, Donald Metzler, Da-Cheng Juan
Sparse Sinkhorn Attention. CoRR (2020)
Arjun Gopalan, Da-Cheng Juan, Cesar Ilharco Magalhaes, Chun-Sung Ferng, Allan Heydon, Chun-Ta Lu, Philip Pham, George Yu
Neural Structured Learning: Training Neural Networks with Structured Signals. KDD (2020)
Da-Cheng Juan, Chun-Ta Lu, Zhen Li, Futang Peng, Aleksei Timofeev, Yi-Ting Chen, Yaxi Gao, Tom Duerig, Andrew Tomkins, Sujith Ravi
Ultra Fine-Grained Image Semantic Embedding. WSDM (2020)
Pranjal Awasthi, George Yu, Chun-Sung Ferng, Andrew Tomkins, Da-Cheng Juan
Adversarial Robustness Across Representation Spaces. CoRR (2020)
Hao-Yun Chen, Jhao-Hong Liang, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Improving Adversarial Robustness via Guided Complement Entropy. ICCV (2019)
Chieh Hubert Lin, Chia-Che Chang, Yu-Sheng Chen, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen
COCO-GAN: Generation by Parts via Conditional Coordinating. CoRR (2019)
Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Complement Objective Training. ICLR (Poster) (2019)
Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh
Natural Adversarial Sentence Generation with Gradient-based Perturbation. CoRR (2019)
Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Complement Objective Training. CoRR (2019)
Hao-Yun Chen, Jhao-Hong Liang, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Improving Adversarial Robustness via Guided Complement Entropy. CoRR (2019)
Chieh Hubert Lin, Chia-Che Chang, Yu-Sheng Chen, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen
COCO-GAN: Generation by Parts via Conditional Coordinating. ICCV (2019)
Trapit Bansal, Da-Cheng Juan, Sujith Ravi, Andrew McCallum
A2N: Attending to Neighbors for Knowledge Graph Inference. ACL (1) (2019)
Hao-Yun Chen, Li-Huang Tsai, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Learning with Hierarchical Complement Objective. CoRR (2019)
Chun-Hao Liu, Da-Cheng Juan, Xuan-An Tseng, Wei Wei, Yu-Ting Chen, Jia-Yu Pan, Shih-Chieh Chang
Hierarchical LSTM: Modeling Temporal Dynamics and Taxonomy in Location-Based Mobile Check-Ins. PAKDD (2) (2019)
Da-Cheng Juan, Chun-Ta Lu, Zhen Li, Futang Peng, Aleksei Timofeev, Yi-Ting Chen, Yaxi Gao, Tom Duerig, Andrew Tomkins, Sujith Ravi
Graph-RISE: Graph-Regularized Image Semantic Embedding. CoRR (2019)
Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh
On the Robustness of Self-Attentive Models. ACL (1) (2019)
An-Chieh Cheng, Jin-Dong Dong, Chi-Hung Hsu, Shu-Huan Chang, Min Sun, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Searching toward pareto-optimal device-aware neural architectures. ICCAD (2018)
Dimitrios Stamoulis, Ermao Cai, Da-Cheng Juan, Diana Marculescu
HyperPower: Power- and memory-constrained hyper-parameter optimization for neural networks. DATE (2018)
Chia-Che Chang, Chieh Hubert Lin, Che-Rung Lee, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen
Escaping from Collapsing Modes in a Constrained Space. CoRR (2018)
An-Chieh Cheng, Chieh Hubert Lin, Da-Cheng Juan, Wei Wei, Min Sun
InstaNAS: Instance-aware Neural Architecture Search. CoRR (2018)
Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun
DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures. CoRR (2018)
Chia-Che Chang, Chieh Hubert Lin, Che-Rung Lee, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen
Escaping from Collapsing Modes in a Constrained Space. ECCV (7) (2018)
Chi-Hung Hsu, Shu-Huan Chang, Da-Cheng Juan, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Shih-Chieh Chang
MONAS: Multi-Objective Neural Architecture Search using Reinforcement Learning. CoRR (2018)
Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun
DPP-Net: Device-Aware Progressive Search for Pareto-Optimal Neural Architectures. ECCV (11) (2018)
Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun
PPP-Net: Platform-aware Progressive Search for Pareto-optimal Neural Architectures. ICLR (Workshop) (2018)
An-Chieh Cheng, Jin-Dong Dong, Chi-Hung Hsu, Shu-Huan Chang, Min Sun, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Searching Toward Pareto-Optimal Device-Aware Neural Architectures. CoRR (2018)
Ermao Cai, Da-Cheng Juan, Dimitrios Stamoulis, Diana Marculescu
NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks. CoRR (2017)
Da-Cheng Juan, Neil Shah, Mingyu Tang, Zhiliang Qian, Diana Marculescu, Christos Faloutsos
M3A: Model, MetaModel and Anomaly Detection for Inter-arrivals of Web Searches and Postings. DSAA (2017)
Dimitrios Stamoulis, Ermao Cai, Da-Cheng Juan, Diana Marculescu
HyperPower: Power- and Memory-Constrained Hyper-Parameter Optimization for Neural Networks. CoRR (2017)
You-Luen Lee, Da-Cheng Juan, Xuan-An Tseng, Yu-Ting Chen, Shih-Chieh Chang
DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters. ECML/PKDD (3) (2017)
Ermao Cai, Da-Cheng Juan, Dimitrios Stamoulis, Diana Marculescu
\emphNeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks. ACML (2017)
You-Luen Lee, Da-Cheng Juan, Xuan-An Tseng, Yu-Ting Chen, Shih-Chieh Chang
DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters. CoRR (2017)
Da-Cheng Juan, Neil Shah, Mingyu Tang, Zhiliang Qian, Diana Marculescu, Christos Faloutsos
M3A: Model, MetaModel, and Anomaly Detection in Web Searches. CoRR (2016)
Jiajia Jiao, Diana Marculescu, Da-Cheng Juan, Yuzhuo Fu
A two-level approximate model driven framework for characterizing Multi-Cell Upsets impacts on processors. Microelectron. J. 48 (2016)
Zhiliang Qian, Da-Cheng Juan, Paul Bogdan, Chi-Ying Tsui, Diana Marculescu, Radu Marculescu
A Support Vector Regression (SVR)-Based Latency Model for Network-on-Chip (NoC) Architectures. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 35 (3) (2016)
Ermao Cai, Da-Cheng Juan, Siddharth Garg, Jinpyo Park, Diana Marculescu
Learning-Based Power/Performance Optimization for Many-Core Systems With Extended-Range Voltage/Frequency Scaling. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 35 (8) (2016)
Jinglan Liu, Da-Cheng Juan, Yiyu Shi
Effective CAD Research in the Sea of Papers. ICCAD (2015)
Jiajia Jiao, Da-Cheng Juan, Diana Marculescu, Yuzhuo Fu
Exploiting component dependency for accurate and efficient soft error analysis via Probabilistic Graphical Models. Microelectron. Reliab. 55 (1) (2015)
Diana Marculescu, Da-Cheng Juan, Guangshuo Liu
Understanding and Using Heterogeneity for High Performance, Energy Efficient Computing: Special Session Extended Abstract. CSCS (2015)
Da-Cheng Juan, Lei Li, Huan-Kai Peng, Diana Marculescu, Christos Faloutsos
Beyond Poisson: Modeling Inter-Arrival Time of Requests in a Datacenter. PAKDD (2) (2014)
Zhiliang Qian, Da-Cheng Juan, Paul Bogdan, Chi-Ying Tsui, Diana Marculescu, Radu Marculescu
A comprehensive and accurate latency model for Network-on-Chip performance analysis. ASP-DAC (2014)
Da-Cheng Juan, Siddharth Garg, Diana Marculescu
Statistical Peak Temperature Prediction and Thermal Yield Improvement for 3D Chip Multiprocessors. ACM Trans. Design Autom. Electr. Syst. 19 (4) (2014)
Zhiliang Qian, Da-Cheng Juan, Paul Bogdan, Chi-Ying Tsui, Diana Marculescu, Radu Marculescu
SVR-NoC: a performance analysis tool for network-on-chips using learning-based support vector regression model. DATE (2013)
Da-Cheng Juan, Siddharth Garg, Jinpyo Park, Diana Marculescu
Learning the optimal operating point for many-core systems with extended range voltage/frequency scaling. CODES+ISSS (2013)
Da-Cheng Juan, Siddharth Garg, Diana Marculescu
Impact of manufacturing process variations on performance and thermal characteristics of 3D ICs: Emerging challenges and new solutions. ISCAS (2013)
Da-Cheng Juan, Yi-Lin Chuang, Diana Marculescu, Yao-Wen Chang
Statistical thermal modeling and optimization considering leakage power variations. DATE (2012)
Da-Cheng Juan, Diana Marculescu
Power-aware performance increase via core/uncore reinforcement control for chip-multiprocessors. ISLPED (2012)
Da-Cheng Juan, Huapeng Zhou, Diana Marculescu, Xin Li
A learning-based autoregressive model for fast transient thermal analysis of chip-multiprocessors. ASP-DAC (2012)
Da-Cheng Juan, Siddharth Garg, Diana Marculescu
Statistical thermal evaluation and mitigation techniques for 3D Chip-Multiprocessors in the presence of process variations. DATE (2011)
Da-Cheng Juan, Yu-Ting Chen, Ming-Chao Lee, Shih-Chieh Chang
An Efficient Wake-Up Strategy Considering Spurious Glitches Phenomenon for Power Gating Designs. IEEE Trans. Very Large Scale Integr. Syst. 18 (2) (2010)
De-Shiuan Chiou, Yu-Ting Chen, Da-Cheng Juan, Shih-Chieh Chang
Sleep Transistor Sizing for Leakage Power Minimization Considering Temporal Correlation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 29 (8) (2010)
De-Shiuan Chiou, Da-Cheng Juan, Yu-Ting Chen, Shih-Chieh Chang
Fine-Grained Sleep Transistor Sizing Algorithm for Leakage Power Minimization. DAC (2007)
Yu-Ting Chen, Da-Cheng Juan, Ming-Chao Lee, Shih-Chieh Chang
An efficient wake-up schedule during power mode transition considering spurious glitches phenomenon. ICCAD (2007)