Fine-Grained Sleep Transistor Sizing Algorithm for Leakage Power Minimization. - De-Shiuan Chiou; Da-Cheng Juan; Yu-Ting Chen 002; Shih-Chieh Chang (DAC, 2007)

An efficient wake-up schedule during power mode transition considering spurious glitches phenomenon. - Yu-Ting Chen 002; Da-Cheng Juan; Ming-Chao Lee; Shih-Chieh Chang (ICCAD, 2007)

Sleep Transistor Sizing for Leakage Power Minimization Considering Temporal Correlation. - De-Shiuan Chiou; Yu-Ting Chen 002; Da-Cheng Juan; Shih-Chieh Chang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2010)

An Efficient Wake-Up Strategy Considering Spurious Glitches Phenomenon for Power Gating Designs. - Da-Cheng Juan; Yu-Ting Chen 002; Ming-Chao Lee; Shih-Chieh Chang (IEEE Trans. Very Large Scale Integr. Syst., 2010)

Statistical thermal evaluation and mitigation techniques for 3D Chip-Multiprocessors in the presence of process variations. - Da-Cheng Juan; Siddharth Garg; Diana Marculescu (DATE, 2011)

A learning-based autoregressive model for fast transient thermal analysis of chip-multiprocessors. - Da-Cheng Juan; Huapeng Zhou; Diana Marculescu; Xin Li 001 (ASP-DAC, 2012)

Statistical thermal modeling and optimization considering leakage power variations. - Da-Cheng Juan; Yi-Lin Chuang; Diana Marculescu; Yao-Wen Chang (DATE, 2012)

Power-aware performance increase via core/uncore reinforcement control for chip-multiprocessors. - Da-Cheng Juan; Diana Marculescu (ISLPED, 2012)

Learning the optimal operating point for many-core systems with extended range voltage/frequency scaling. - Da-Cheng Juan; Siddharth Garg; Jinpyo Park; Diana Marculescu (CODES+ISSS, 2013)

SVR-NoC: a performance analysis tool for network-on-chips using learning-based support vector regression model. - Zhiliang Qian; Da-Cheng Juan; Paul Bogdan; Chi-Ying Tsui; Diana Marculescu; Radu Marculescu (DATE, 2013)

Impact of manufacturing process variations on performance and thermal characteristics of 3D ICs: Emerging challenges and new solutions. - Da-Cheng Juan; Siddharth Garg; Diana Marculescu (ISCAS, 2013)

A comprehensive and accurate latency model for Network-on-Chip performance analysis. - Zhiliang Qian; Da-Cheng Juan; Paul Bogdan; Chi-Ying Tsui; Diana Marculescu; Radu Marculescu (ASP-DAC, 2014)

Beyond Poisson: Modeling Inter-Arrival Time of Requests in a Datacenter. - Da-Cheng Juan; Lei Li 005; Huan-Kai Peng; Diana Marculescu; Christos Faloutsos (PAKDD (2), 2014)

Statistical Peak Temperature Prediction and Thermal Yield Improvement for 3D Chip Multiprocessors. - Da-Cheng Juan; Siddharth Garg; Diana Marculescu (ACM Trans. Design Autom. Electr. Syst., 2014)

A Learning-Based Framework Incorporating Domain Knowledge for Performance Modeling. - Da-Cheng Juan (2014)

Understanding and Using Heterogeneity for High Performance, Energy Efficient Computing: Special Session Extended Abstract. - Diana Marculescu; Da-Cheng Juan; Guangshuo Liu (CSCS, 2015)

Effective CAD Research in the Sea of Papers. - Jinglan Liu; Da-Cheng Juan; Yiyu Shi 001 (ICCAD, 2015)

Exploiting component dependency for accurate and efficient soft error analysis via Probabilistic Graphical Models. - Jiajia Jiao; Da-Cheng Juan; Diana Marculescu; Yuzhuo Fu (Microelectron. Reliab., 2015)

M3A: Model, MetaModel, and Anomaly Detection in Web Searches. - Da-Cheng Juan; Neil Shah; Mingyu Tang; Zhiliang Qian; Diana Marculescu; Christos Faloutsos (CoRR, 2016)

A two-level approximate model driven framework for characterizing Multi-Cell Upsets impacts on processors. - Jiajia Jiao; Diana Marculescu; Da-Cheng Juan; Yuzhuo Fu (Microelectron. J., 2016)

Learning-Based Power/Performance Optimization for Many-Core Systems With Extended-Range Voltage/Frequency Scaling. - Ermao Cai; Da-Cheng Juan; Siddharth Garg; Jinpyo Park; Diana Marculescu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2016)

A Support Vector Regression (SVR)-Based Latency Model for Network-on-Chip (NoC) Architectures. - Zhiliang Qian; Da-Cheng Juan; Paul Bogdan; Chi-Ying Tsui; Diana Marculescu; Radu Marculescu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2016)

emphNeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks. - Ermao Cai; Da-Cheng Juan; Dimitrios Stamoulis; Diana Marculescu (ACML, 2017)

M3A: Model, MetaModel and Anomaly Detection for Inter-arrivals of Web Searches and Postings. - Da-Cheng Juan; Neil Shah; Mingyu Tang; Zhiliang Qian; Diana Marculescu; Christos Faloutsos (DSAA, 2017)

DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters. - You-Luen Lee; Da-Cheng Juan; Xuan-An Tseng; Yu-Ting Chen 002; Shih-Chieh Chang (ECML/PKDD (3), 2017)

NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks. - Ermao Cai; Da-Cheng Juan; Dimitrios Stamoulis; Diana Marculescu (CoRR, 2017)

HyperPower: Power- and memory-constrained hyper-parameter optimization for neural networks. - Dimitrios Stamoulis; Ermao Cai; Da-Cheng Juan; Diana Marculescu (DATE, 2018)

Escaping from Collapsing Modes in a Constrained Space. - Chia-Che Chang; Chieh Hubert Lin; Che-Rung Lee; Da-Cheng Juan; Wei Wei 019; Hwann-Tzong Chen (ECCV (7), 2018)

DPP-Net: Device-Aware Progressive Search for Pareto-Optimal Neural Architectures. - Jin-Dong Dong; An-Chieh Cheng; Da-Cheng Juan; Wei Wei 019; Min Sun 001 (ECCV (11), 2018)

Searching toward pareto-optimal device-aware neural architectures. - An-Chieh Cheng; Jin-Dong Dong; Chi-Hung Hsu; Shu-Huan Chang; Min Sun 001; Shih-Chieh Chang; Jia-Yu Pan; Yu-Ting Chen 002; Wei Wei 019; Da-Cheng Juan (ICCAD, 2018)

PPP-Net: Platform-aware Progressive Search for Pareto-optimal Neural Architectures. - Jin-Dong Dong; An-Chieh Cheng; Da-Cheng Juan; Wei Wei 019; Min Sun 001 (ICLR (Workshop), 2018)

MONAS: Multi-Objective Neural Architecture Search using Reinforcement Learning. - Chi-Hung Hsu; Shu-Huan Chang; Da-Cheng Juan; Jia-Yu Pan; Yu-Ting Chen 002; Wei Wei 019; Shih-Chieh Chang (CoRR, 2018)

A2N: Attending to Neighbors for Knowledge Graph Inference. - Trapit Bansal; Da-Cheng Juan; Sujith Ravi; Andrew McCallum (ACL (1), 2019)

On the Robustness of Self-Attentive Models. - Yu-Lun Hsieh; Minhao Cheng; Da-Cheng Juan; Wei Wei 019; Wen-Lian Hsu; Cho-Jui Hsieh (ACL (1), 2019)

Improving Adversarial Robustness via Guided Complement Entropy. - Hao-Yun Chen; Jhao-Hong Liang; Shih-Chieh Chang; Jia-Yu Pan; Yu-Ting Chen 002; Wei Wei 019; Da-Cheng Juan (ICCV, 2019)

COCO-GAN: Generation by Parts via Conditional Coordinating. - Chieh Hubert Lin; Chia-Che Chang; Yu-Sheng Chen; Da-Cheng Juan; Wei Wei 019; Hwann-Tzong Chen (ICCV, 2019)

Complement Objective Training. - Hao-Yun Chen; Pei-Hsin Wang; Chun-Hao Liu; Shih-Chieh Chang; Jia-Yu Pan; Yu-Ting Chen 002; Wei Wei 019; Da-Cheng Juan (ICLR (Poster), 2019)

Hierarchical LSTM: Modeling Temporal Dynamics and Taxonomy in Location-Based Mobile Check-Ins. - Chun-Hao Liu; Da-Cheng Juan; Xuan-An Tseng; Wei Wei 019; Yu-Ting Chen 002; Jia-Yu Pan; Shih-Chieh Chang (PAKDD (2), 2019)

Graph-RISE: Graph-Regularized Image Semantic Embedding. - Da-Cheng Juan; Chun-Ta Lu; Zhen Li 028; Futang Peng; Aleksei Timofeev; Yi-Ting Chen; Yaxi Gao; Tom Duerig; Andrew Tomkins; Sujith Ravi (CoRR, 2019)

Natural Adversarial Sentence Generation with Gradient-based Perturbation. - Yu-Lun Hsieh; Minhao Cheng; Da-Cheng Juan; Wei Wei 019; Wen-Lian Hsu; Cho-Jui Hsieh (CoRR, 2019)

Learning with Hierarchical Complement Objective. - Hao-Yun Chen; Li-Huang Tsai; Shih-Chieh Chang; Jia-Yu Pan; Yu-Ting Chen 002; Wei Wei 019; Da-Cheng Juan (CoRR, 2019)

InstaNAS: Instance-Aware Neural Architecture Search. - An-Chieh Cheng; Chieh Hubert Lin; Da-Cheng Juan; Wei Wei 019; Min Sun 001 (AAAI, 2020)

Low-Dimensional Hyperbolic Knowledge Graph Embeddings. - Ines Chami; Adva Wolf; Da-Cheng Juan; Frederic Sala; Sujith Ravi; Christopher Ré (ACL, 2020)

Remix: Rebalanced Mixup. - Hsin-Ping Chou; Shih-Chieh Chang; Jia-Yu Pan; Wei Wei 019; Da-Cheng Juan (ECCV Workshops (6), 2020)

AirConcierge: Generating Task-Oriented Dialogue via Efficient Large-Scale Knowledge Retrieval. - Chieh-Yang Chen; Pei-Hsin Wang; Shih-Chieh Chang; Da-Cheng Juan; Wei Wei 019; Jia-Yu Pan (EMNLP (Findings), 2020)

Question Answering with Long Multiple-Span Answers. - Ming Zhu 015; Aman Ahuja; Da-Cheng Juan; Wei Wei 019; Chandan K. Reddy (EMNLP (Findings), 2020)

Sparse Sinkhorn Attention. - Yi Tay; Dara Bahri; Liu Yang; Donald Metzler; Da-Cheng Juan (ICML, 2020)

Neural Structured Learning: Training Neural Networks with Structured Signals. - Arjun Gopalan; Da-Cheng Juan; Cesar Ilharco Magalhaes; Chun-Sung Ferng; Allan Heydon; Chun-Ta Lu; Philip Pham; George Yu (KDD, 2020)

Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization. - Hung-Jen Chen 002; An-Chieh Cheng; Da-Cheng Juan; Wei Wei 019; Min Sun 001 (NeurIPS, 2020)

Ultra Fine-Grained Image Semantic Embedding. - Da-Cheng Juan; Chun-Ta Lu; Zhen Li 028; Futang Peng; Aleksei Timofeev; Yi-Ting Chen; Yaxi Gao; Tom Duerig; Andrew Tomkins; Sujith Ravi (WSDM, 2020)

Calibrated BatchNorm: Improving Robustness Against Noisy Weights in Neural Networks. - Li-Huang Tsai; Shih-Chieh Chang; Yu-Ting Chen 002; Jia-Yu Pan; Wei Wei 019; Da-Cheng Juan (CoRR, 2020)

HyperGrid: Efficient Multi-Task Transformers with Grid-wise Decomposable Hyper Projections. - Yi Tay; Zhe Zhao 001; Dara Bahri; Donald Metzler; Da-Cheng Juan (CoRR, 2020)

Graph Autoencoders with Deconvolutional Networks. - Jia Li 009; Tomas Yu; Da-Cheng Juan; Arjun Gopalan; Hong Cheng 001; Andrew Tomkins (CoRR, 2020)

"Does it Matter When I Think You Are Lying?" Improving Deception Detection by Integrating Interlocutor's Judgements in Conversations. - Huang-Cheng Chou; Woan-Shiuan Chien; Da-Cheng Juan; Chi-Chun Lee (ACL/IJCNLP (Findings), 2021)

Uncertainty Modeling of Emerging Device based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search. - Zheyu Yan; Da-Cheng Juan; Xiaobo Sharon Hu; Yiyu Shi 001 (ASP-DAC, 2021)

Adversarial Robustness Across Representation Spaces. - Pranjal Awasthi; George Yu; Chun-Sung Ferng; Andrew Tomkins; Da-Cheng Juan (CVPR, 2021)

HyperGrid Transformers: Towards A Single Model for Multiple Tasks. - Yi Tay; Zhe Zhao 001; Dara Bahri; Donald Metzler; Da-Cheng Juan (ICLR, 2021)

OmniNet: Omnidirectional Representations from Transformers. - Yi Tay; Mostafa Dehghani 001; Vamsi Aribandi; Jai Prakash Gupta 001; Philip Pham; Zhen Qin 001; Dara Bahri; Da-Cheng Juan; Donald Metzler (ICML, 2021)

Synthesizer: Rethinking Self-Attention for Transformer Models. - Yi Tay; Dara Bahri; Donald Metzler; Da-Cheng Juan; Zhe Zhao 001; Che Zheng (ICML, 2021)

Neural Structured Learning: Training Neural Networks with Structured Signals. - Arjun Gopalan; Da-Cheng Juan; Cesar Ilharco Magalhaes; Chun-Sung Ferng; Allan Heydon; Chun-Ta Lu; Philip Pham; George Yu; Yicheng Fan; Yueqi Wang (WSDM, 2021)

Switch Spaces: Learning Product Spaces with Sparse Gating. - Shuai Zhang 007; Yi Tay; Wenqi Jiang 001; Da-Cheng Juan; Ce Zhang 001 (CoRR, 2021)

CARLS: Cross-platform Asynchronous Representation Learning System. - 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; et al. (CoRR, 2021)

Meta-CPR: Generalize to Unseen Large Number of Agents with Communication Pattern Recognition Module. - Wei-Cheng Tseng; Wei Wei 019; Da-Cheng Juan; Min Sun 001 (CoRR, 2021)

Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generation. - 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 (CoRR, 2022)

Attributed Text Generation via Post-hoc Research and Revision. - 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 (CoRR, 2022)

RARR: Researching and Revising What Language Models Say, Using Language Models. - 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 (ACL (1), 2023)

LayerNAS: Neural Architecture Search in Polynomial Complexity. - Yicheng Fan; Dana Alon; Jingyue Shen; Daiyi Peng; Keshav Kumar; Yun Long; Xin Wang 016; Fotis Iliopoulos; Da-Cheng Juan; Erik Vee (CoRR, 2023)

Substance or Style: What Does Your Image Embedding Know? - Cyrus Rashtchian; Charles Herrmann; Chun-Sung Ferng; Ayan Chakrabarti; Dilip Krishnan; Deqing Sun; Da-Cheng Juan; Andrew Tomkins (CoRR, 2023)

SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models. - Jianyi Zhang; Da-Cheng Juan; Cyrus Rashtchian; Chun-Sung Ferng; Heinrich Jiang; Yiran Chen 001 (NeurIPS, 2024)

Think or Remember? Detecting and Directing LLMs Towards Memorization or Generalization. - Yi-Fu Fu; Yu-Chieh Tu; Tzu-Ling Cheng; Cheng-Yu Lin; Yi-Ting Yang; Heng-Yi Liu; Keng-Te Liao; Da-Cheng Juan; Shou-De Lin (CoRR, 2024)

Sufficient Context: A New Lens on Retrieval Augmented Generation Systems. - Hailey Joren; Jianyi Zhang; Chun-Sung Ferng; Da-Cheng Juan; Ankur Taly; Cyrus Rashtchian (ICLR, 2025)

DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback. - Jiao Sun; Deqing Fu; Yushi Hu; Su Wang 001; Royi Rassin; Da-Cheng Juan; Dana Alon; Charles Herrmann; Sjoerd van Steenkiste; Ranjay Krishna; Cyrus Rashtchian (NAACL (Long Papers), 2025)