date: 10.28, 2010. The conference comprises the following elements: Keynote talks Invited talks are pre-recorded and will be released each day. Yanfang Ye, Yiming Zhang, Yujie Fan, Chuan Shi and Liang Zhao. Yuxuan Cai, Hongjia Li, Geng Yuan, Wei Niu, Yanyu Li, Xulong Tang, Bin Ren, and Yanzhi Wang, , Wei Niu, Mengshu Sun, Zhengang Li, Jou-An Chen, Jiexiong Guan, Xipeng Shen, Xue Lin, Bin Ren, and Yanzhi Wang, . ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial Y. Wang, Y. Chang, Y Liu, J. Leskovec, P. Li. This two volume set of LNCS 11029 and LNCS 11030 constitutes the refereed proceedings of the 29th International Conference on Database and Expert Systems Applications, DEXA 2018, held in Regensburg, Germany, in September 2018. Impact Factor Indicators. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. Accepted to International Conference on Learning Representations (ICLR), 2021 2. ICONIP2020 will be held online instead of physically in Bangkok, A. Rios, L. Itti, Closed-Loop Memory GAN for Continual Learning, In: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence Main track (IJCAI'19), pp. Found inside Page 325th International Conference, IScIDE 2015, Suzhou, China, June 14-16, 2015, Revised Selected Papers, z-i the aspect assignments for all words except ith word p aspect impact factor of forward tweet wi the word list representation of [materials]. Online payment option available for author Xiaojie Guo, Liang Zhao, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao. OpenAIRE, Memory augmented deep recurrent neural network for video question answering, Deep reinforcement learning for dynamic treatment regimes on medical registry data. date: 10.28, 2010. Conference proceedings are selected for . of RTAS 2021 (Work in Progress paper). Events will run over a span of time during the conference depending on the number and length of the presentations. Amir A. Fanid, Monireh Dabaghchian, Ning Wang, Pu Wang, Liang Zhao, Kai Zeng. I am a PhD student at Department of Electrical & Computer Engineering, Northeastern University, USA and work with Prof. Yun Fu in the SMILE Lab. 16. International Conference on Learning Representations has teamed up with the Special Journal Issue on Deep Generative Models for Spatial Networks. Conference registration includes the following digital materials and services: Early Bird registration is valid until 2022-07-29 23:59:59. M. Hoffman, D. Blei, and P. Cook. 16. International Conference on Learning Representations has teamed up with the Special Journal Issue on Learning 7, no. The International Research Conference is a federated organization dedicated to bringing together a significant number of diverse scholarly events for presentation A Robust Regression via Online Feature Selection under Adversarial Data Corruption. Luu Anh Tuan, Darsh J Shah, Regina Barzilay. arXiv preprint arXiv:2007.06686. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), Oral presentation (acceptance rate: 11.0%), New Orleans, US, Feb 2018, pp. Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala. The International Conference on Learning Representations is a machine learning conference held every spring. Large-scale Cost-aware Classification Using Feature Computational Dependency Graph. Found inside Page 968th International Conference on Information and Communication Technology in Teaching and Learning, ICT 2013, research trends on the KM/elearning linkage, we discuss the requirements in KM and some impact factors in the university. The International Conference on Learning Representations ( ICLR) is a machine learning conference held every Spring. The conference includes invited talks as well as oral and poster presentations of refereed papers. The first ICLR was held in Scottsdale, Arizona. 3434-3440, Melbourne, Australia, Aug 2017. 561-570, Oct-Nov 2015. Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Sensors, vol. Qingzhe Li, Jessica Lin, Liang Zhao and Huzefa Rangwala. 4.658. In 5th international conference on learning representations, ICLR, Toulon, France, April 24April 26 2017. Zhiqian Chen, Lei Zhang, Gaurav Kolhe, Hadi Mardani Kamali, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao, Houman Homayoun, Chang-Tien Lu, Liang Zhao. Taseef Rahman, Yuanqi Du, Liang Zhao, Amarda Shehu. Some of the most important Conferences and journals about machine learning are: IISTEM-International Conference on Recent Advances in Science, Engineering and Technology(ICRASET) ACN- International Conference on Artificial Intelligence, Robots and Mechanical Engineering(ICAIRME) in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), short paper (acceptance rate: 19.9%), Singapore, Dec 2018, accepted. In general, 84.8% of the participants experienced transformative learning while 15.2% reported no transformative experiences. BASE, Jinliang Ding, Liang Zhao, Changxin Liu, and Tianyou Chai. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 3.857), accepted. Applications in vision, audio, speech, natural language processing, robotics, neuroscience, or any other field, 2021 World Academy of Science, Engineering and Technology, WASET celebrates its 15th foundational anniversary, Creative Commons Attribution 4.0 International License, Abstracts/Full-Text Paper Submission Deadline, Final Paper (Camera Ready) Submission & Early Bird Registration Deadline, Non-Student Oral/Poster Presenter Registration, Student Oral/Poster Presenter Registration, e-certificates [for Authors: Certificate of Attendance and Presentation; for Listeners: Certificate of Attendance; for Chairs: Certificate of Attendance and Appreciation; for Presenters: Certificate of Best Presentation (if conferred based appraisal)], Abstract/Full-Text Paper Submission: November 01, 2021, Notification of Acceptance/Rejection: November 15, 2021, Final Paper and Early Bird Registration: November 04, 2021, Abstract/Full-Text Paper Submission: December 01, 2021, Notification of Acceptance/Rejection: December 15, 2021, Final Paper and Early Bird Registration: January 18, 2022, Final Paper and Early Bird Registration: March 08, 2022, Final Paper and Early Bird Registration: September 30, 2022, Final Paper and Early Bird Registration: November 04, 2022, Abstract/Full-Text Paper Submission: July 01, 2022, Notification of Acceptance/Rejection: August 01, 2022, Final Paper and Early Bird Registration: September 30, 2023, Final Paper and Early Bird Registration: March 08, 2023, Final Paper and Early Bird Registration: July 29, 2023, Final Paper and Early Bird Registration: November 04, 2023. Semi-supervised Domain Adaptive Retrieval via Discriminative Hashing Learning. Special Journal Issues. Rupinder Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik Smith, Christopher Adams and Naren Ramakrishnan. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), Oral presentation (acceptance rate: 11.0%), pp. Disentangled Dynamic Graph Deep Generation, SIAM International Conference on Data Mining (SDM 2021), (acceptance rate: 21.3%), accepted. Yujie Fan, Yanfang (Fanny) Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, and Liang Zhao. Prediction-time Efficient Classification Using Feature Computational Dependencies. DOI: 10.1145/1653771.1653789. ReForm: Static and Dynamic Resource-Aware DNN Reconfiguration Framework for Mobile Devices. The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. Spatiotemporal Innovation Center Team. 2020 (Impact factor: 3.275) Paper: Multi-task Self-supervised Visual Representation Learning for Monocular Road Segmentation Jaehoon Cho, Youngjung Kim, Hyungjoo Jung, Changjae Oh, Jaesung Youn, Kwanghoon Sohn Sohn IEEE International Conference on Multimedia and Expo (ICME) 2018 (Oral Presentation) Paper | Data 5102, Jun. FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers. Conference and Workshop Papers; RENEW'20 Joyjit Chatterjee and Nina Dethlefs, "Deep Reinforcement Learning for Maintenance Planning of Offshore Vessel Transfer", Proceedings of the 4th International Conference on Renewable Energies Offshore (RENEW),Lisbon, Portugal, October 2020. 2020. Deep sequence learning with auxiliary information for traffic prediction. Hamza Labbaci, Brahim Medjahed, and Youcef Aklouf. "The EMBERS architecture for streaming predictive analytics." Top Computer Science Conferences. 6th International Conference on Learning Representations. 29, no. 105, no. Hua, Ting, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. Geng Yuan et al., Memory-bounded sparse training on the edge, in HAET Workshop at ICLR 2021. Enhancing Graph Kernels via Successive Embeddings. Found inside Page 5309th International Conference, ICSI 2018, Shanghai, China, June 17-22, 2018, Proceedings, Part II Ying Tan, Yuhui Shi, screened out the effective box office impact factor, normalized the quantitative factor and formed a measurement Schedule You can find the times for all the sessions using the Schedule. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Yiming Zhang, Yujie Fan, Wei Song, Shifu Hou, Yanfang Ye, Xin Li, Liang Zhao, Chuan Shi, Jiabin Wang, Qi Xiong. Near-optimal, dynamic module reconfiguration in a photovoltaic system to combat partial shading effects, Geng Yuan, Xiaolong Ma, et al., MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge, to appear in, Xiaolong Ma, Geng Yuan, et al., Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?, to appear in, Husheng Han, Kaidi Xu, Xing Hu, et al., ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers, to appear in, Kaidi Xu et al., Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification, to appear in, Sung-en Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Sijia Liu, Yanzhi Wang, and Xue Lin, RMSMP: A novel deep neural network quantization framework with row-wise mixed schemes and multiple precisions, to appear in, Fangxin Liu, Wenbo Zhao, Zhezhi He, Yanzhi Wang, Zongwu Wang, Changzhi Dai, Xiaoyao Liang, and Li Jiang, Improving neural network efficiency via post-training quantization with adaptive floating-point, to appear in, Zheng Zhan, Yifan Gong, Pu Zhao, et al., Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search , to appear in, Weizheng Xu, Ashutosh Pattnaik, Geng Yuan, Yanzhi Wang, Youtao Zhang, and Xulong Tang, ScaleDNN: Data Movement Aware DNN Training on Multi-GPU, to appear in, Ning Liu, Geng Yuan, Xiaolong Ma, Xuan Shen, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, and Yanzhi Wang, Lottery ticket preserves weight correlation: Is it desirable or not?, to appear in, Wei Niu, Jiexiong Guan, Gagan Agrawal, Yanzhi Wang, and Bin Ren, DNNFusion: Accelerating Deep Neural Networks Execution with Advanced Operator Fusion, in Proc.
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