Linxuan Zhang, Nelson J Amaral, Di Niu

TransFusion: End-to-End Transformer Acceleration via Graph Fusion and Pipelining

in Proceedings of the 58th IEEE/ACM International Symposium on Microarchitecture (MICRO 2025), Seoul, Korea, October 18-22, 2025.

Hongxuan Liu, Juliana Y. Leung, Di Niu

MethaneS2CM: A Dataset for Multispectral Deep Methane Emission Detection

in Proceedings of the 31st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2025), Toronto, Ontario, Canada, August 3–7, 2025

DOI: 10.1145/3711896.3737415

M Shakerdargah, S Lu, C Gao, D Niu

MAS-Attention: Memory-Aware Stream Processing for Attention Acceleration on Resource-Constrained Edge Devices [pdf]

MLSys 2025, Santa Clara, CA, May 2025

KG Mills, M Salameh, R Chen, N Hassanpour, W Lu, D Niu

QuaSeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models [pdf]

AAAI 2025, Philadelphia, Pennsylvania, February 2025

Liyao Jiang, Negar Hassanpour, Mohammad Salameh, Mohammadreza Samadi, Jiao He, Fengyu Sun, Di Niu

PixelMan: Consistent Object Editing with Diffusion Models via Pixel Manipulation and Generation [pdf]

AAAI 2025, Philadelphia, Pennsylvania, February 2025

M Samadi, FX Han, M Salameh, H Wu, F Sun, C Zhou, D Niu

FunEditor: Achieving Complex Image Edits via Function Aggregation with Diffusion Models [pdf]

AAAI 2025, Philadelphia, Pennsylvania, February 2025

Jiuding Yang, Shengyao Lu, Weidong Guo, Xiangyang Li, Kaitong Yang, Yu Xu, and Di Niu

TaCIE: Enhancing Instruction Comprehension in Large Language Models through Task-Centred Instruction Evolution [https://aclanthology.org/2025.coling-main.57/]

In Proceedings of the 31st International Conference on Computational Linguistics (COLING 2025), pages 855–869, Abu Dhabi, UAE, January 2025. Association for Computational Linguistics.

Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh, Di Niu. “Learning Truncated Causal History Model for Video Restoration,” in Advances in Neural Information Processing Systems (NeurIPS 2024), 37, pp.27584-27615, Vancouver, December 2024. [pdf]

Yakun Yu, Shi-ang Qi, Baochun Li, Di Niu. “PepRec: Progressive Enhancement of Prompting for Recommendation,” in EMNLP 2024, Miami, November 2024. [pdf]

Jiuding Yang, Hui Liu, Weidong Guo, Zhuwei Rao, Yu Xu, and Di Niu

Reassess Summary Factual Inconsistency Detection with Large Language Model.

In Proceedings of the 1st Workshop on Towards Knowledgeable Language Models (KnowLLM 2024), pages 27–31, Bangkok, Thailand. Association for Computational Linguistics.

[pdf]

Weidong Guo, Jiuding Yang, Kaitong Yang, Xiangyang Li, Zhuwei Rao, Yu Xu, and Di Niu. Instruction fusion: advancing prompt evolution through hybridization [pdf]

in Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024).

Jerry Chen, Ruiqing Tian and Di Niu. “Tuner: A New Approach For 3D Semantic

Segmentation Using Federated Architecture,” in Proceedings of the IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom 2024). [pdf]

Shengyao Lu, Bang Liu, Keith G Mills, Jiao He, and Di Niu. “EiG-Search: Generating edge-induced subgraphs for GNN explanation in linear time,” in Proceedings of The Forty-first International Conference on Machine Learning (ICML 2024). [pdf]

Keith G. Mills, Fred X. Han, Mohammad Salameh, Shengyao Lu, Chunhua Zhou, Jiao He, Fengyu Sun, and Di Niu. “Building Optimal Neural Architectures using Interpretable Knowledge,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024), pages 5726-5735. [pdf]

Qikai Lu, Di Niu, Mohammadamin Samadi Khoshkho, and Baochun Li. “HyperFLoRA: Federated Learning with Instantaneous Personalization,” in Proceedings of the 2024 SIAM International Conference on Data Mining (SDM 2024) (pp. 824-832). [pdf]

Mingjun Zhao, Liyao Jiang, Yakun Yu, Xinmin Wang, Yi Yuan, Zheng Wei, Di Niu. “DimReg: Embedding Dimension Search via Regularization for Recommender Systems,” in Proceedings of the 2024 SIAM International Conference on Data Mining (SDM 2024) (pp. 562-570). [pdf]

Jian Ma, Mingjun Zhao. Chen Chen, Ruichen Wang, Di Niu, Haonan Lu, Xiaodong Lin. “GlyphDraw: Learning to Draw Chinese Characters in Image Synthesis Models Coherently,” arXiv:2303.17870v2 [cs.CV] [pdf]

Shengyao Lu, Keith G Mills, Jiao He, Bang Liu, and Di Niu. “GOAt: Explaining graph neural networks via graph output attribution,” in Proceedings of The Twelfth International Conference on Learning Representations (ICLR 2024). [pdf]

Sijia Chen, Baochun Li, Di Niu. “Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models,” in Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024). [pdf]

Mohammad Salameh, Keith G. Mills, Negar Hassanpour, Fred X. Han, Shuting Zhang, Wei Lu, Shangling Jui, Chunhua Zhou, Fengyu Sun and Di Niu. “AutoGO: Automated Computation Graph Optimization for Neural Network Evolution,” in Advances in Neural Information Processing Systems (NeurIPS 2023), vol. 36, pages 74455-74477, New Orleans, Louisiana, December 10-16, 2023. [pdf]

Bahador Rashidi, Chao Gao, Shan Lu, Zhisheng Wang, Chunhua Zhou, Di Niu and Fengyu Sun. “UNICO: Unified Hardware Software Co-Optimization for Robust  Neural Network Acceleration,” in Proceedings of the 56th IEEE/ACM International Symposium on Microarchitecture (MICRO 2023), Toronto, Canada, October 28-November 1, 2023. [pdf]

Yakun Yu, Shi-ang Qi, Jiuding Yang, Liyao Jiang and Di Niu. “iHAS: Instance-wise Hierarchical Architecture Search for Deep Learning Recommendation Models,” in Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM) 2023, Birmingham, UK, October 21-25, 2023. [pdf]

Jiuding Yang, Jinwen Luo, Weidong Guo, Jerry Chen, Di Niu, and Yu Xu. “Mulco: Recognizing Chinese Nested Named Entities through Multiple Scopes,” in Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023), pp. 2980-2989, Birmingham, UK, October 21-25, 2023. [pdf]

Ruichen Chen, Shengyao Lu, Mohamed A. Elgammal, Peter Chun, Vaughn Betz, Di Niu. “VPR-Gym: A Platform for Exploring AI Techniques in FPGA Placement Optimization,” in Proceedings of the 33rd International Conference on Field-Programmable Logic and Applications (FPL 2023). [pdf]

Liyao Jiang, Chenglin Li, Haolan Chen, Xiaodong Gao, Xinwang Zhong, Yang Qiu, Shani Ye, and Di Niu. “AdSEE: Investigating the Impact of Image Style Editing on Advertisement Attractiveness,” in Applied Data Science Track of the 29th ACM SIGKDD Conference ON Knowledge Discovery and Data Mining (KDD 2023), Long Beach, CA, August 6-10, 2023. [pdf]

Keith G. Mills, Muhammad F. Qharabagh, Weichen Qiu, Fred X. Han, Mohammad Salameh, Wei Lu, Shangling Jui and Di Niu. “Applying Graph Explanation to Operator Fusion,” in Work-in-Progress (WIP) poster session at the 60th Design Automation Conference (DAC), San Francisco, CA, July 9-13, 2023. [slides]

Jiuding Yang, Yakun Yu, Di Niu, Weidong Guo and Yu Xu. “ConFEDE: Contrastive Feature Decomposition for Multimodal Sentiment Analysis,” in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023). [pdf]

Jiuding Yang, Jinwen Luo, Weidong Guo, Di Niu and Yu Xu. “Exploiting Hierarchically Structured Categories in Fine-grained Chinese Named Entity Recognition,” in the Findings of the 61st Annual Meeting of the Association for Computational Linguistics (Findings of ACL 2023). [pdf]

Yakun Yu, Mingjun Zhao, Shi-ang Qi, Feiran Sun, Baoxun Wang, Weidong Guo, Xiaoli Wang, Lei Yang and Di Niu. “ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis,” in the Findings of the 61st Annual Meeting of the Association for Computational Linguistics (Findings of ACL 2023). [pdf]

Mingjun Zhao, Yakun Yu, Xiaoli Wang, Lei Yang, Di Niu. “Search-Map-Search: a Frame Selection Paradigm for Action Recognition,” in Proceedings of IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) 2023, Vancouver, Canada, June 18-22, 2023. [pdf]

Mingjun Zhao, Mengzhen Wang, Yinglong Ma, Di Niu, Haijiang Wu. “CEIL: A General ClassificationEnhanced Iterative Learning Framework for Text Clustering,” in Proceedings of the Web Conference (WWW) 2023, Austin, Texas, April 30-May 4, 2023. [pdf]

Yakun Yu, Jiuding Yang, Weidong Guo, Hui Liu, Yu Xu, Di Niu. "TCR: Short Video Title Generation and Cover Selection with Attention Refinement," in Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2023. [pdf]

Yuchen Zhang, Mingjun Zhao, Chenglin Li, Weiyu Tou, Haolan Chen, Di Niu, Cunxiang Yin, Yancheng He, Fei Guo. ”Online Volume Optimization for Notifications via Long Short-Term Value Modeling,” in Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2023. [pdf]

Alexander Detkov, Mohammad Salameh, Muhammad Fetrat, Jialin Zhang, Robin Luwei, Shangling Jui, Di Niu. “Reparameterization through Spatial Gradient Scaling,” in Proceedings of the Eleventh International Conference on Learning Representations (ICLR 2023), Kigali Rwanda, May 1-5, 2023. [pdf]

Shan Lu, Mingjun Zhao, Songling Yuan, Xiaoli Wang, Lei Yang, Di Niu. “BDA: Bandit-based Transferable AutoAugment,” in Proceedings of SIAM International Conference on Data Mining (SDM) 2023. [pdf]

Peng Liu, Yi Liu, Rui Zhu, Linglong Kong, Bei Jiang, Di Niu. “Optimal Smooth Approximation for Quantile Matrix Factorization,” in Proceedings of SIAM International Conference on Data Mining (SDM) 2023. [pdf]

Fred X. Han, Keith Mills, Fabian Chudak, Parsa Riahi, Mohammad Salameh, Jialin Zhang, Wei Lu, Shangling Jui, Di Niu. “A General-Purpose Transferable Predictor for Neural Architecture Search,” in Proceedings of SIAM International Conference on Data Mining (SDM) 2023. [pdf]

Keith Mills, Di Niu, Mohammad Salameh, Weichen Qiu, Fred X. Han, Puyuan Liu, Jialin Zhang, Wei Lu, Shangling Jui. “AIO-P: Expanding Neural Performance Predictors Beyond Image Classification,” in Proceedings of AAAI 2023. [pdf]

Keith Mills, Fred X. Han, Jialin Zhang, Fabian Chudak, Ali Safari, Mohammad Salameh, Wei Lu, Shangling Jui, Di Niu. “GENNAPE: Towards Generalized Neural Architecture Performance Estimators,” in Proceedings of AAAI 2023. [pdf]

Chenglin Li, Yuanzhen Xie, Chenyun Yu, Bo Hu, Zang Li, Guoqiang Shu, Xiaohu Qie, Di Niu. “One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation,” in Proceedings of ACM International Conference on Web Search and Data Mining (WSDM 2023). [pdf]

Jinwen Luo, Jiuding Yang, Weidong Guo, Chenglin Li, Di Niu, and Yu Xu. “MatRank: Text Re-ranking by Latent Preference Matrix,” in Findings of the Association for Computational Linguistics: EMNLP 2022, pages 2011–2023, Abu Dhabi, United Arab Emirates, December 2022. [pdf]

Jerry Chen, Jonah Chen, Ruiqing Tian, Di Niu. "Estimating 3D Indoor Object Dimensions," in the Proceedings of 2022 IEEE 2nd IoT Vertical and Topical Summit for Tourism (IoTT) (IoT-VTST'22). [pdf]

Mingjun Zhao, Shan Lu, Zixuan Wang, Xiaoli Wang, Di Niu. "LA3: Efficient Label-Aware AutoAugment," in ECCV 2022. [pdf]

Jiuding Yang, Weidong Guo, Bang Liu, Yakun Yu, Chaoyue Wang, Jinwen Luo, Linglong Kong, Di Niu, Zhen Wen. "TAG: Toward Accurate Social Media Content Tagging with a Concept Graph," in Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022). [pdf]

Shengyao Lu, Bang Liu, Keith G Mills, SHANGLING JUI, Di Niu. “R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning,” in the Tenth International Conference on Learning Representations (ICLR 2022), Apr 25 2022.

Chenglin Li, Mingjun Zhao, Huanming Zhang, Chenyun Yu, Lei Cheng, Guoqiang Shu, Beibei Kong, and Di Niu. “RecGURU: Adversarial Learning of Generalized User Representations for Cross-Domain Recommendation,” in Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining (WSDM 2022), February 21–25, 2022, Tempe, AZ, USA. https://doi.org/10.1145/3488560.3498388

Keith G. Mills, Fred X. Han, Jialin Zhang, Seyed Saeed Changiz Rezaei, Fabian Chudak, Wei Lu, Shuo Lian, Shangling Jui and Di Niu. “Profiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search,” applied full paper in proceedings of the 30th annual ACM International Conference on Information and Knowledge Management (CIKM’21), 2021.

Keith G. Mills, Fred X. Han, Mohammad Salameh, Seyed Saeed Changiz Rezaei, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui and Di Niu. “L2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning,” full paper in proceedings of the 30th annual ACM International Conference on Information and Knowledge Management (CIKM’21), 2021.

Kunxun Qi, Ruoxu Wang, Qikai Lu, Xuejiao Wang, Ning Jing, Di Niu and Haolan Chen. “Dual Learning for Query Generation and Query Selection in Query Feeds Recommendation”, applied full paper in proceedings of the 30th annual ACM International Conference on Information and Knowledge Management (CIKM’21), 2021.

Weidong Guo, Mingjun Zhao, Lusheng Zhang, Di Niu, Jinwen Luo, Zhenhua Liu, Zhenyang Li, Jianbo Tang. “LICHEE: Improving Language Model Pre-training with Multi-grained Tokenization,” in Findings of ACL, 2021.

Seyed S.C. Rezaei, Fred X. Han, Di Niu, Mohammad Salameh, Keith Mills, Shuo Lian, Wei Lu, Shangling Jui. “Generative Adversarial Neural Architecture Search,” in Proceedings of IJCAI 2021.

Chenglin Li, Di Niu, Bei Jiang, Xiao Zuo, Jianming Yang. “Meta-HAR: Federated Representation Learning for Human Activity Recognition,” in the Web Conference (WWW) 2021.

Mingjun Zhao, Haijiang Wu, Di Niu, Zixuan Wang, Xiaoli Wang. “Verdi: Quality Estimation and Error Detection for Bilingual Corpora, ” in the Web Conference (WWW) 2021.

Yaochen Hu, Peng Liu, Keshi Ge, Linglong Kong, Bei Jiang, Di Niu. "Learning Privately over Distributed Features: An ADMM Sharing Approach," in NeurIPS-20 Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL 2020).

Tong Mo, Yakun Yu, Mohammad Salameh, Di Niu, Shangling Jui. “Neural Architecture Search For Keyword Spotting,” in InterSpeech 2020.

Fred X. Han, Di Niu, Haolan Chen, Weidong Guo, Shengli Yan, Bowei Long. “Meta-Learning for Query Conceptualization at Web Scale,” full paper in KDD 2020 Applied Data Science Track.

Bang Liu, Weidong Guo, Di Niu, Jingwen Luo, Chaoyue Wang, Zhen Wen, Yu Xu. “GIANT: Scalable Creation of a Web-scale Ontology," to appear in ACM SIGMOD Conference (SIGMOD) 2020, Portland, Oregon, USA.

Bang Liu, Haojie Wei, Di Niu, Haolan Chen, Yancheng He. "Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus," to appear in the Web Conference (WWW) 2020, Taipei, April 20-24, 2020.

Hao Wang, Zakhary Kaplan, Di Niu, Baochun Li. "Optimizing Federated Learning on Non-IID Data with Reinforcement Learning," to appear in IEEE INFOCOM 2020, Beijing, China, April 27-30, 2020.

Mingjun Zhao, Haijiang Wu, Di Niu, Xiaoli Wang. "Reinforced Curriculum Learning on Pre-trained Neural Machine Translation Models," in Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20), New York, Feb 7-12, 2020.

Bang Liu, Di Niu, Haojie Wei, Jinghong Lin, Yancheng He, Kunfeng Lai, Yu Xu. “Matching Article Pairs with Graphical Decomposition and Convolutions,” in ACL 2019, Florence, Italy.

Yaochen Hu, Di Niu, Jianming Yang and Shengping Zhou. “FDML: A Collaborative Machine Learning Framework for Distributed Features,” to appear in KDD2019 proceedings, accepted for oral presentation at KDD2019 Applied Data Science Track. (acceptance rate 6.4%)

Fred X. Han, Di Niu, Haolan Chen, Kunfeng Lai, Yancheng He and Yu Xu. “A Deep Generative Approach to Search Extrapolation and Recommendation,” to appear in KDD2019 proceedings, accepted for poster presentation at KDD2019 Applied Data Science Track. (acceptance rate 14.3%)

Bang Liu, Weidong Guo, Di Niu, Chaoyue Wang, Shunnan Xu, Jinghong Lin, Kunfeng Lai and Yu Xu. “A User-Centered Concept Mining System for Query and Document Understanding at Tencent,” to appear in KDD2019 proceedings, accepted for poster presentation at KDD2019 Applied Data Science Track. (acceptance rate 14.3%)

Bang Liu, Mingjun Zhao, Di Niu, Kunfeng Lai, Yancheng He, Haojie Wei and Yu Xu. “Learning to Generate Questions by Learning What not to Generate,” in the Web Conference 2019 (WWW 2019), San Francisco, May 13-17, 2019.

Fred X. Han, Di Niu, Kunfeng Lai, Weidong Guo, Yancheng He and Yu Xu. “Inferring Search Queries from Web Documents via a Graph-Augmented Sequence to Attention Network,” in the Web Conference 2019 (WWW 2019), San Francisco, May 13-17, 2019.

Hao Wang, Di Niu, Baochun Li. “Distributed Machine Learning with a Serverless Architecture,” to appear in IEEE INFOCOM 2019, Paris, France, April 29-May2, 2019.

Hao Huang, Qian Yan, Ting Gan, Di Niu, Wei Lu, Yunjun Gao. “Learning Diffusions without Timestamps,” in AAAI 2019, Honolulu, Hawaii, Jan 27-Feb 1, 2019.

Yaochen Hu, Di Niu and Jianming Yang. “A Fast Linear Computational Framework for User Action Prediction in Tencent MyApp,” to appear in the Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM) 2018, Turin, Italy, October 22-26, 2018.

Ting Zhang, Bang Liu, Di Niu, Kunfeng Lai and Yu Xu. “Multiresolution Graph Attention Networks for Relevance Matching,” to appear in the Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM) 2018, Turin, Italy, October 22-26, 2018.

Hao Wang, Di Niu, Baochun Li. “Dynamic and Decentralized Global Analytics via Machine Learning,” to appear in the Proceedings of the ACM Symposium on Cloud Computing 2018 (SoCC 2018), October 11-13, 2018.

Haolan Chen, Fred X. Han, Di Niu, Dong Liu, Kunfeng Lai, Chenglin Wu and Yu Xu. “MIX: Multi-Channel Information Crossing for Text Matching,” in the Proceedings of the 24th

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), London, UK, August 19-23, 2018.

Bang Liu, Ting Zhang, Fred X. Han, Di Niu, Kunfeng Lai and Yu Xu. “Matching Natural Language Sentences with Hierarchical Sentence Factorization,” in the Proceedings of the Web Conference 2018 (WWW 2018), Lyon, France, April 23-27, 2018. (acceptance rate: 14.8%)

Bang Liu, Borislav Mavrin, Linglong Kong, Di Niu. “Recover Fine-Grained Spatial Data from Coarse Aggregation,” to appear in the Proceedings of IEEE International Conference on Data Mining (ICDM) 2017. (acceptance rate: 19.9%)

Bang Liu, Di Niu, Kunfeng Lai, Linglong Kong, Yu Xu. “Growing Story Forest Online from Massive Breaking News,” in the Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM 2017).

Yaochen Hu, Yushi Wang, Bang Liu, Di Niu, Cheng Huang. “Latency Reduction and Load Balancing in Coded Storage Systems,” in the Proceedings of ACM Symposium on Cloud Computing (SoCC) 2017. (acceptance rate: 23.6%, one of 48 accepted)

Wenxin Li, Di Niu, Yinan Liu, Shuhao Liu, Baochun Li. “Joint Routing and Batch Sizing in Wide-Area Stream Processing Systems,” in the Proceedings of the 14th International Conference on Autonomic Computing (ICAC 2017), Columbus, Ohio, July 17-21, 2017.

Rui Zhu, Di Niu, Baochun Li, Zongpeng Li. "Optimal Multicast in Virtualized Datacenter Networks with Software Switches," in the Proceedings of IEEE INFOCOM 2017. (acceptance rate: 20.9%)

Rui Zhu, Di Niu, Zongpeng Li. “Robust Web Service Recommendation via Quantile Matrix Factorization,” in the Proceedings of IEEE INFOCOM 2017. (acceptance rate: 20.9%)

Rui Zhu, Di Niu, Linglong Kong, Zongpeng Li. “Expectile Matrix Factorization for Extreme Data Analysis,” in the Proceedings of AAAI 2017, San Francisco, CA, Feb 4-9, 2017. (acceptance rate: 24.6%)

Bang Liu, Borislav Mavrin, Di Niu, Linglong Kong. “House Price Modeling over Heterogeneous Regions with Hierarchical Spatial Functional Analysis,” in the Proceedings of IEEE International Conference on Data Mining (ICDM) 2016, Barcelona, Spain, Dec 12-15, 2016. (acceptance rate: 19.6%)

Haolan Chen, Di Niu, Kunfeng Lai, Yu Xu, Masoud Ardakani. “Separating-Plane Factorization Models: Scalable Recommendation from One-Class Implicit Feedback,” in the Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM 2016). (acceptance rate 19.8%) (doi>http://dx.doi.org/10.1145/2983323.2983348)

Rui Zhu, Di Niu, Zongpeng Li. “Online Code Rate Adaptation in Cloud Storage Systems with Multiple Erasure Codes,” in 28th Biennial Symposium on Communications (BSC 2016), Kelowna, British Columbia, June 5-8, 2016.

Soham Sinha, Di Niu, Zhi Wang, Paul Lu. "Mitigating Routing Inefficiencies to Cloud-Storage Providers: A Case Study," in IEEE Workshop on Dependable Parallel, Distributed and Network-Centric Systems, in conjunction with IPDPS, Chicago, May, 2016.

Yaochen Hu, Di Niu. “Reducing Access Latency in Erasure Coded Cloud Storage with Local Block Migration,” in the Proceedings of IEEE INFOCOM 2016, San Francisco, April 10-15, 2016.

Bang Liu, Di Niu, Zongpeng Li, H. Vicky Zhao. “Network Latency Prediction for Personal Devices: Distance-Feature Decomposition from 3D Sampling,” in the Proceedings of IEEE INFOCOM 2015, Hong Kong, April 26-May 1, 2015.

Rui Zhu, Di Niu, Baochun Li. “Min-Cost Live Webcast under Joint Pricing of Data, Congestion and Virtualized Servers,” in the Proceedings of NETGCOOP 2014, Trento, Italy. [Slides (ppt)]

Majid Khabbazian, Di Niu. "Achieving Optimal Block Pipelining in Organized Network Coded Gossip," in the Proceedings of the 34th International Conference on Distributed Computing Systems (ICDCS 2014), Madrid, Spain, June 30-July 3, 2014.
(Acceptance rate: 13%)

Di Niu, Baochun Li. “Congestion-Aware Internet Pricing for Media Streaming,” in the Proceedings of the 3rd Workshop on Smart Data Pricing (SDP), Toronto, Canada, May 2, 2014.

Shuopeng Zhang, Di Niu, Yaochen Hu, Fangming Liu. “Server Selection and Topology Control for Multi-Party Video Conferences,” in the Proceedings of ACM NOSSDAV 2014, Singapore, March 19-21, 2014. 

Wei Wang, Di Niu, Baochun Li, Ben Liang. “Dynamic Cloud Resource Reservation via Cloud Brokerage,” in the Proceedings of the 33rd International Conference on Distributed Computing Systems (ICDCS 2013), Philadelphia, Pennsylvania, July 8-11, 2013. [Technical Report]
(Acceptance rate: 13%)

Di Niu, Baochun Li. "An Efficient Distributed Algorithm for Resource Allocation in Large-Scale Coupled Systems," in the Proceedings of IEEE INFOCOM 2013 Main Conference, Turin, Italy, April 14-19, 2013.

(Acceptance rate: 17%)

Di Niu, Chen Feng, Baochun Li. “Pricing Cloud Bandwidth Reservations under Demand Uncertainty,” in the Proceedings of ACM SIGMETRICS/Performance 2012, London, UK, June 11-15, 2012. [Technical Report] [Slides (ppt)] [Slides (pdf)]

(Acceptance rate: 15.27%)

Di Niu, Chen Feng, Baochun Li. “A Theory of Cloud Bandwidth Pricing for Video-on-Demand Providers,” in the Proceedings of IEEE INFOCOM 2012 Main Conference, Orlando, Florida, March 25-30, 2012. [Slides]

(Acceptance rate: 18%)

Di Niu, Hong Xu, Baochun Li, Shuqiao Zhao. “Quality-Assured Cloud Bandwidth Auto-Scaling for Video-on-Demand Applications,” in the Proceedings of IEEE INFOCOM 2012 Main Conference, Orlando, Florida, March 25-30, 2012. [Slides]

(Acceptance rate: 18%)

Di Niu, Hong Xu, Baochun Li, Shuqiao Zhao. “Risk Management for Video-on-Demand Servers leveraging Demand Forecast,” in the Proceedings of ACM Multimedia 2011, Scottsdale, Arizona, November 28 – December 1, 2011.

Di Niu, Baochun Li, Shuqiao Zhao. “Understanding Demand Volatility in Large VoD Systems,” in the Proceedings of ACM NOSSDAV 2011, Vancouver, Canada, June, 2011.

Di Niu, Baochun Li. “Asymptotic Optimality of Randomized Peer-to-Peer Broadcast with Network Coding,” in the Proceedings of IEEE INFOCOM 2011 Main Conference, Shanghai, China, April 10-15, 2011.

(Acceptance rate: 15.96%)

Di Niu, Zimu Liu, Baochun Li, Shuqiao Zhao. “Demand Forecast and Performance Prediction in Peer-Assisted On-Demand Streaming Systems,” in the Proceedings of IEEE INFOCOM 2011 Mini-Conference, Shanghai, China, April 10-15, 2011.

(Acceptance rate: 23.42%)

Di Niu, Baochun Li, Shuqiao Zhao. "Self-Diagnostic Peer-Assisted Video Streaming through a Learning Framework," in the Proceedings of ACM Multimedia 2010, Florence, Italy, October 25-29, 2010. [Slides]

(Systems track full paper acceptance rate: 15%)

Di Niu, Baochun Li. "Topological Properties Affect the Power of Network Coding in Decentralized Broadcast," in the Proceedings of IEEE INFOCOM 2010 Main Conference, San Diego, California, March 15-19, 2010.

(Acceptance rate: 17.52%)

Di Niu, Baochun Li. “Asymptotic Rate Limits for Randomized Broadcasting with Network Coding,” in the Proceedings of the 47th Annual Allerton Conference on Communication, Control, and Computing, UIUC, Monticello, Illinois, September 30 - October 2, 2009.

Fangming Liu, Bo Li, Lili Zhong, Baochun Li, Di Niu. "How Do P2P Streaming Systems Scale Over Time Under a Flash Crowd?" to appear in the Proceedings of the International Workshop on Peer-to-Peer Systems (IPTPS 2009), Boston, MA, April 21, 2009.

(Acceptance rate: 20%)

Di Niu, Baochun Li. “Circumventing Server Bottlenecks: Indirect Large-Scale P2P Data Collection,” in the Proceedings of the 28th International Conference on Distributed Computing Systems (ICDCS 2008), Beijing, China, June 17-20, 2008.

(Acceptance rate: 16%)

Di Niu, Baochun Li. “On the Resilience-Complexity Tradeoff of Network Coding in Dynamic P2P Networks,” in the Proceedings of the 15th IEEE International Workshop on Quality of Service (IWQoS 2007), pp. 38-46, Chicago, Illinois, June 21-22, 2007.

(Acceptance rate: 20.6%)