{"id":650565,"date":"2020-04-17T09:15:15","date_gmt":"2020-04-17T16:15:15","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&p=650565"},"modified":"2020-06-15T07:16:54","modified_gmt":"2020-06-15T14:16:54","slug":"iclr-2020","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/iclr-2020\/","title":{"rendered":"Microsoft at ICLR 2020"},"content":{"rendered":"

Website:<\/strong> ICLR 2020 (opens in new tab)<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Microsoft is a Silver sponsor of the Eighth International Conference on Learning Representations (ICLR) this year. ICLR is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"msr_startdate":"2020-04-26","msr_enddate":"2020-04-30","msr_location":"Virtual","msr_expirationdate":"","msr_event_recording_link":"","msr_event_link":"","msr_event_link_redirect":false,"msr_event_time":"","msr_hide_region":false,"msr_private_event":false,"footnotes":""},"research-area":[13556,13562,13545],"msr-region":[256048],"msr-event-type":[197941],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-650565","msr-event","type-msr-event","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-computer-vision","msr-research-area-human-language-technologies","msr-region-global","msr-event-type-conferences","msr-locale-en_us"],"msr_about":"Website:<\/strong> ICLR 2020<\/a>","tab-content":[{"id":0,"name":"About","content":"Microsoft is a Silver sponsor of the Eighth International Conference on Learning Representations (ICLR) this year. ICLR is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.\r\n\r\nICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics."},{"id":1,"name":"Booth schedule","content":"

Microsoft Booth Schedule at ICLR<\/h2>\r\nTalk to our experts and learn more about our research and open opportunities.\r\n

Monday, April 27<\/h3>\r\n

Live Demos<\/h4>\r\n\r\n\r\n\r\n
23:00 \u2013 24:00 GMT<\/td>\r\nRick Calle, AI Research Business Director<\/em> - Challenge: Preventing the Next AI Winter. What Can AI Researchers Do To Improve AI Computing Energy?<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
10:00 \u2013 11:00 GMT<\/td>\r\nKatja Hofmann<\/a>, Principal Researcher<\/em><\/td>\r\n<\/tr>\r\n
13:00 \u2013 14:00 GMT<\/td>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
15:00 \u2013 16:00 GMT<\/td>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
16:00 \u2013 17:00 GMT<\/td>\r\nAmy Siebenthaler, University\/PhD Recruiting<\/em>\r\nDevin Gunson, GTA Industry Recruiting, Quantum & Deep Learning<\/em>\r\nNeel Sundaresan, Partner Director, Cloud and AI<\/em><\/td>\r\n<\/tr>\r\n
22:00 \u2013 23:00 GMT<\/td>\r\nAashna Garg, Applied Scientist<\/em>\r\nDawn Drain, Data Scientist<\/em>\r\nRoshanak Zilouchian, Senior Data & Applied Scientist<\/em><\/td>\r\n<\/tr>\r\n
23:00 \u2013 24:00 GMT<\/td>\r\nColin Clement, Data Scientist<\/em>\r\nDevin Gunson, GTA Industry Recruiting, Quantum & Deep Learning<\/em><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Tuesday, April 28<\/h3>\r\n

Live Demos<\/h4>\r\n\r\n\r\n\r\n\r\n\r\n
16:00 \u2013 17:00 GMT<\/td>\r\nAlex Polozov<\/a>, Senior Researcher<\/em> - RAT-SQL: Database Question Answering via Neural Semantic Parsing of Text to SQL<\/td>\r\n<\/tr>\r\n
22:00 \u2013 23:00 GMT<\/td>\r\nKevin Ashley, Sr. Software Engineer<\/em> - How to use Microsoft Azure ML for Sports, Health and Fitness<\/td>\r\n<\/tr>\r\n
23:00 \u2013 24:00 GMT<\/td>\r\nRick Calle, AI Research Business Director<\/em> - Challenge: Preventing the Next AI Winter. What Can AI Researchers Do To Improve AI Computing Energy?<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
4:00 \u2013 5:00 GMT<\/td>\r\nAlexey Svyatkovskiy, Senior Data Scientist, Cloud and AI<\/em><\/td>\r\n<\/tr>\r\n
7:00 \u2013 8:00 GMT<\/td>\r\nHiske Overweg<\/a>, Researcher<\/em><\/td>\r\n<\/tr>\r\n
13:00 \u2013 14:00 GMT<\/td>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
15:00 \u2013 16:00 GMT<\/td>\r\nKamil Ciosek<\/a>, Senior Researcher<\/em>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
16:00 \u2013 17:00 GMT<\/td>\r\nAmy Siebenthaler, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
22:00 \u2013 23:00 GMT<\/td>\r\nAashna Garg, Applied Scientist<\/em>\r\nColin Clement, Data Scientist<\/em>\r\nDawn Drain, Data Scientist<\/em>\r\nDevin Gunson, GTA Industry Recruiting, Quantum & Deep Learning<\/em><\/td>\r\n<\/tr>\r\n
23:00 \u2013 24:00 GMT<\/td>\r\nAlex Polozov<\/a>, Senior Researcher<\/em>\r\nDevin Gunson, GTA Industry Recruiting, Quantum & Deep Learning<\/em>\r\nRoshanak Zilouchian, Senior Data & Applied Scientist<\/em><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Wednesday, April 29<\/h3>\r\n

Live Demos<\/h4>\r\n\r\n\r\n\r\n\r\n
19:00 \u2013 20:00 GMT<\/td>\r\nAlex Polozov<\/a>, Senior Researcher<\/em> - RAT-SQL: Database Question Answering via Neural Semantic Parsing of Text to SQL<\/td>\r\n<\/tr>\r\n
23:00 \u2013 24:00 GMT<\/td>\r\nRick Calle, AI Research Business Director<\/em> - Challenge: Preventing the Next AI Winter. What Can AI Researchers Do To Improve AI Computing Energy?<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
4:00 \u2013 5:00 GMT<\/td>\r\nAlexey Svyatkovskiy, Senior Data Scientist, Cloud and AI<\/em><\/td>\r\n<\/tr>\r\n
14:00 \u2013 15:00 GMT<\/td>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
15:00 \u2013 16:00 GMT<\/td>\r\nAmy Siebenthaler, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
19:00 \u2013 20:00 GMT<\/td>\r\nNeel Sundaresan, Partner Director, Cloud and AI<\/em>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
22:00 \u2013 23:00 GMT<\/td>\r\nAashna Garg, Applied Scientist<\/em>\r\nColin Clement, Data Scientist<\/em>\r\nDawn Drain, Data Scientist<\/em>\r\nDevin Gunson, GTA Industry Recruiting, Quantum & Deep Learning<\/em><\/td>\r\n<\/tr>\r\n
23:00 \u2013 24:00 GMT<\/td>\r\nAlex Polozov<\/a>, Senior Researcher<\/em>\r\nDevin Gunson, GTA Industry Recruiting, Quantum & Deep Learning<\/em><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Thursday, April 30<\/h3>\r\n

Live Demos<\/h4>\r\n\r\n\r\n\r\n
23:00 \u2013 24:00 GMT<\/td>\r\nRick Calle, AI Research Business Director<\/em> - Challenge: Preventing the Next AI Winter. What Can AI Researchers Do To Improve AI Computing Energy?<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
7:00 \u2013 8:00 GMT<\/td>\r\nHiske Overweg<\/a>, Researcher<\/em><\/td>\r\n<\/tr>\r\n
13:00 \u2013 14:00 GMT<\/td>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
15:00 \u2013 16:00 GMT<\/td>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
16:00 \u2013 17:00 GMT<\/td>\r\nVikas Gosain, University\/PhD Recruiting<\/em><\/td>\r\n<\/tr>\r\n
22:00 \u2013 23:00 GMT<\/td>\r\nAlex Polozov<\/a>, Senior Researcher<\/em>\r\nDawn Drain, Data Scientist<\/em>\r\nDevin Gunson, GTA Industry Recruiting, Quantum & Deep Learning<\/em><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>"},{"id":2,"name":"Accepted papers","content":"AMRL: Aggregated Memory For Reinforcement Learning<\/strong><\/a>\r\nJacob Beck,\u00a0Kamil Ciosek<\/a>,\u00a0Sam Devlin<\/a>, Sebastian Tschiatschek,\u00a0Cheng Zhang<\/a>,\u00a0Katja Hofmann<\/a>\r\nMon Session 1 (05:00-07:00 GMT) | Mon Session 3 (12:00-14:00 GMT)\r\n\r\nAdaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation<\/strong><\/a>\r\nXinjie Fan,\u00a0Yizhe Zhang<\/a>, Zhendong Wang, Mingyuan Zhou\r\nTues Session 3 (12:00-14:00 GMT) | Tues Session 5 (20:00-22:00 GMT)\r\n\r\nConservative Uncertainty Estimation By Fitting Prior Networks<\/strong><\/a>\r\nKamil Ciosek<\/a>,\u00a0Vincent Fortuin<\/a>,\u00a0Ryota Tomioka<\/a>,\u00a0Katja Hofmann<\/a>,\u00a0Richard Turner<\/a>\r\nMon Session 2 (08:00-10:00 GMT) | Mon Session 3 (12:00-14:00 GMT)\r\n\r\nDeep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds<\/strong><\/a>\r\nJordan T. Ash, Chicheng Zhang,\u00a0Akshay Krishnamurthy<\/a>,\u00a0John Langford<\/a>,\u00a0Alekh Agarwal<\/a>\r\nWed Session 3 (12:00-14:00 GMT) | Wed Session 4 (17:00-19:00 GMT)\r\n\r\nDeformable Kernels: Adapting Effective Receptive Fields for Object Deformation<\/strong><\/a>\r\nHang Gao<\/strong>, Xizhou Zhu<\/strong>,\u00a0Steve Lin<\/a>, Jifeng Dai<\/strong>\r\nWed Session 4 (17:00-19:00 GMT) | Wed Session 5 (20:00-22:00 GMT)\r\n\r\nDisagreement-Regularized Imitation Learning<\/strong><\/a>\r\nKiante Brantley, Wen Sun<\/strong>,\u00a0Mikael Henaff<\/a>\r\nMon Session 2 (08:00-10:00 GMT) | Mon Session 4 (17:00-19:00 GMT)\r\n\r\nEffect of Activation Functions on the Training of Overparametrized Neural Nets<\/strong><\/a>\r\nAbhishek Panigrahi, Abhishek Shetty,\u00a0Navin Goyal<\/a>\r\nTues Session 2 (08:00-10:00 GMT) | Tues Session 3 (12:00-14:00 GMT)\r\n\r\nFSNet: Compression of Deep Convolutional Neural Networks by Filter Summary<\/strong><\/a>\r\nYingzhen Yang, Jiahui Yu,\u00a0Nebojsa Jojic<\/a>, Jun Huan, Thomas S. Huang\r\nTues Session 4 (17:00-19:00 GMT) [Video Chat] | Tues Session 5 (20:00-22:00 GMT)\r\n\r\nFreeLB: Enhanced Adversarial Training for Natural Language Understanding<\/strong><\/a>\r\nChen Zhu, Yu Cheng<\/strong>, Zhe Gan<\/strong>, Siqi Sun, Tom Goldstein,\u00a0Jingjing Liu<\/a>\r\nThurs Session 4 (17:00-19:00 GMT) | Thurs Session 5 (20:00-22:00 GMT)\r\n\r\nGraph Constrained Reinforcement Learning for Natural Language Action Spaces<\/strong><\/a>\r\nPrithviraj Ammanabrolu,\u00a0Matthew Hausknecht<\/a>\r\nMon Session 1 (05:00-07:00 GMT) | Mon Session 2 (08:00-10:00 GMT)\r\n\r\nIncorporating BERT into Neural Machine Translation<\/strong><\/a>\r\nJinhua Zhu,\u00a0Yingce Xia<\/a>, Lijun Wu,\u00a0Di He<\/a>,\u00a0Tao Qin<\/a>, Wengang Zhou, Houqiang Li,\u00a0Tie-Yan Liu<\/a>\r\nTues Session 2 (08:00-10:00 GMT) | Tues Session 3 (12:00-14:00 GMT)\r\n\r\nLearning Space Partitions for Nearest Neighbor Search<\/strong><\/a>\r\nYihe Dong, Piotr Indyk,\u00a0Ilya Razenshteyn<\/a>, Tal Wagner\r\nMon Session 1 (05:00-07:00 GMT) [Video Chat] | Mon Session 2 (08:00-10:00 GMT)\r\n\r\nLocality And Compositionality In Zero-Shot Learning<\/strong><\/a>\r\nTristan Sylvain, Linda Petrini,\u00a0Devon Hjelm<\/a>\r\nTues Session 4 (17:00-19:00 GMT) | Tues Session 5 (20:00-22:00 GMT)\r\n\r\nLow-Resource Knowledge-Grounded Dialogue Generation<\/strong><\/a>\r\nXueliang Zhao,\u00a0Wei Wu<\/a>, Chongyang Tao, Can Xu<\/strong>, Dongyan Zhao, Rui Yan\r\nThurs Session 1 (05:00-07:00 GMT) | Thurs Session 2 (08:00-10:00 GMT)\r\n\r\nMACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius<\/strong><\/a>\r\nRuntian Zhai, Chen Dan,\u00a0Di He<\/a>, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang\r\nTues Session 1 (05:00-07:00 GMT) | Tues Session 3 (12:00-14:00 GMT)\r\n\r\nOn the Variance of the Adaptive Learning Rate and Beyond<\/strong><\/a>\r\nLiyuan Liu, Haoming Jiang, Pengcheng He<\/strong>, Weizhu Chen<\/strong>,\u00a0Xiaodong Liu<\/a>,\u00a0Jianfeng Gao<\/a>,\u00a0Jiawei Han\r\nTues Session 3 (12:00-14:00 GMT) | Tues Session 5 (20:00-22:00 GMT)\r\n\r\nRaCT: Toward Amortized Ranking-Critical Training For Collaborative Filtering<\/strong><\/a>\r\nSam Lobel,\u00a0Chunyuan Li<\/a>,\u00a0Jianfeng Gao<\/a>, Lawrence Carin\r\nTues Session 4 (17:00-19:00 GMT) | Tues Session 5 (20:00-22:00 GMT)\r\n\r\nSelf-Adversarial Learning with Comparative Discrimination for Text Generation<\/strong><\/a>\r\nWangchunshu Zhou<\/strong>,\u00a0Tao Ge<\/a>, Ke Xu,\u00a0Furu Wei<\/a>,\u00a0Ming Zhou<\/a>\r\nThurs Session 2 (08:00-10:00 GMT) | Thurs Session 3 (12:00-14:00 GMT)\r\n\r\nTransformer-XH: Multi-evidence Reasoning with Extra Hop Attention<\/strong><\/a>\r\nChen Zhao,\u00a0Chenyan Xiong<\/a>,\u00a0Corby Rosset<\/a>, Xia Song<\/strong>,\u00a0Paul Bennett<\/a>, Saurabh Tiwary<\/strong>\r\nThurs Session 1 (05:00-07:00 GMT) | Thurs Session 3 (12:00-14:00 GMT)\r\n\r\nUnsupervised Clustering using Pseudo-semi-supervised Learning<\/strong><\/a>\r\nDivam Gupta,\u00a0Ramachandran Ramjee<\/a>,\u00a0Nipun Kwatra<\/a>,\u00a0Muthian Sivathanu<\/a>\r\nMon Session 4 (17:00-19:00 GMT) | Mon Session 5 (20:00-22:00 GMT)\r\n\r\nVL-BERT: Pre-training of Generic Visual-Linguistic Representations<\/strong><\/a>\r\nWeijie Su, Xizhou Zhu<\/strong>,\u00a0Yue Cao<\/a>,\u00a0Bin Li<\/a>, Lewei Lu<\/strong>,\u00a0Furu Wei<\/a>, Jifeng Dai<\/strong>\r\nTues Session 1 (05:00-07:00 GMT) | Tues Session 3 (12:00-14:00 GMT)\r\n\r\nVariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning<\/strong><\/a>\r\nLuisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal,\u00a0Katja Hofmann<\/a>, Shimon Whiteson\r\nThurs Session 2 (08:00-10:00 GMT) | Thurs Session 3 (12:00-14:00 GMT)"},{"id":3,"name":"#AlchemyFriends","content":"Print your own copy<\/a> of Alchemy with Friends to play at home. Share your favorite card combinations using #AlchemyFriends on Twitter, Facebook, or Instagram.\r\n\r\n\"Animated<\/a>\r\n\r\n
[msr-button text=\"Print Alchemy with Friends\" url=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/12\/Alchemy-with-Friends-Print-at-Home.pdf\" new-window=\"true\" ]<\/div>\r\n
<\/div>\r\n