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The AAAI-13 Conference Workshops

Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Bui, Diane J. Cook, Juan Cortés, Christopher Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting (+11 others)
2013 The AI Magazine  
The AAAI-13 Workshop Program, a part of the 27th AAAI Conference on Artificial Intelligence, was held Sunday and Monday, July 14–15, 2013 at the Hyatt Regency Bellevue Hotel in Bellevue, Washington, USA  ...  Using Artificial Intelligence (WS-13-09); Intelligent Robotic Systems (WS-13-10); Intelligent Techniques for Web Personalization and Recommendation (WS-13-11); Learning Rich Representations from Low-Level  ...  An alternate approach is for rich representations to be learned autonomously from low-level sensor data.  ... 
doi:10.1609/aimag.v34i4.2511 fatcat:lv4sqkibebcfpmu7ne64fenqt4

Collective intelligence

Thomas W. Malone
2007 2007 International Symposium on Collaborative Technologies and Systems  
First, we are grateful to all the authors of the articles for prompt responses and the members of the editorial review board for timely and thorough reviews. The board included Ioannis Anagnostopou-  ...  In 2013, the 27th AAAI will take place from July 14-18 in Bellevue, Washington, USA.  ...  Workshop/Tutorial submission: March 15, 2013 Paper submission: April 26, 2013 Acceptance notification: June 17, 2013 Final version due: July 1, 2013 KI Conference: September 16-20, 2013 ••• MC1 Nonlinear  ... 
doi:10.1109/cts.2007.4621716 fatcat:h3ii3n6pwbg5zhc6qkj2fv7egi

Collective Intelligence [chapter]

2009 Computational Intelligence  
First, we are grateful to all the authors of the articles for prompt responses and the members of the editorial review board for timely and thorough reviews. The board included Ioannis Anagnostopou-  ...  In 2013, the 27th AAAI will take place from July 14-18 in Bellevue, Washington, USA.  ...  Workshop/Tutorial submission: March 15, 2013 Paper submission: April 26, 2013 Acceptance notification: June 17, 2013 Final version due: July 1, 2013 KI Conference: September 16-20, 2013 ••• MC1 Nonlinear  ... 
doi:10.1109/9780470544297.ch17 fatcat:w5fcyebwqzgubjg2d3tutqvp7m

Collective Intelligence [chapter]

2014 Encyclopedia of Social Network Analysis and Mining  
First, we are grateful to all the authors of the articles for prompt responses and the members of the editorial review board for timely and thorough reviews. The board included Ioannis Anagnostopou-  ...  In 2013, the 27th AAAI will take place from July 14-18 in Bellevue, Washington, USA.  ...  Workshop/Tutorial submission: March 15, 2013 Paper submission: April 26, 2013 Acceptance notification: June 17, 2013 Final version due: July 1, 2013 KI Conference: September 16-20, 2013 ••• MC1 Nonlinear  ... 
doi:10.1007/978-1-4614-6170-8_100480 fatcat:cesty3mz5vbilmtfx3gagqi7dq

Robot Learning From Randomized Simulations: A Review

Fabio Muratore, Fabio Ramos, Greg Turk, Wenhao Yu, Michael Gienger, Jan Peters
2022 Frontiers in Robotics and AI  
We provide a comprehensive review of sim-to-real research for robotics, focusing on a technique named "domain randomization" which is a method for learning from randomized simulations.  ...  Therefore, state-of-the-art approaches learn in simulation where data generation is fast as well as inexpensive and subsequently transfer the knowledge to the real robot (sim-to-real).  ...  “PILCO: a Model-Based and Data-Efficient Approach to Policy Search,” in International Conference on Machine Learning (ICML), June 28 - July 2 (Bellevue, Washington, USA, 465–472.  ... 
doi:10.3389/frobt.2022.799893 pmid:35494543 pmcid:PMC9038844 fatcat:f7bytfvmgjfnllmnuy74ywnxau

Learning Better Representations for Audio-Visual Emotion Recognition with Common Information

Fei Ma, Wei Zhang, Yang Li, Shao-Lun Huang, Lin Zhang
2020 Applied Sciences  
One challenge of this problem is how to efficiently extract feature representations from audio and visual modalities.  ...  Specifically, we design an audio network and a visual network to extract the feature representations from audio and visual data respectively, and then employ a fusion network to combine the extracted features  ...  Multimodal deep learning. In Proceedings of the 28th International Conference on Machine Learning (ICML-11), Bellevue, WA, USA, 28 June–2 July 2011; pp. 689–696. [Google Scholar] Sun, S.  ... 
doi:10.3390/app10207239 fatcat:iqfdpdejwfhdvcjtu47hskgtt4