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ORCIDAAAI Spring Symposia 2017: Palo Alto, CA, USA
- 2017 AAAI Spring Symposia, Stanford University, Palo Alto, California, USA, March 27-29, 2017. AAAI Press 2017
1 - Artificial Intelligence for the Social Good
- Oliver Bendel:
LADYBIRD: The Animal-Friendly Robot Vacuum Cleaner. - Oliver Bendel, Kevin Schwegler, Bradley Richards:
Towards Kant Machines. - Malay Bhattacharyya:
In Search of Health Doubles. - Sujoy Chatterjee, Anirban Mukhopadhyay, Malay Bhattacharyya:
Smart City Planning with Constrained Crowd Judgment Analysis. - Arnaud Delaunay, Jean Guérin:
Wandering Detection Within an Embedded System for Alzheimer Suffering Patients. - Virginia Dignum, Frank Dignum:
Societal Challenges Need Social Agents. - Jason Remington Parham, Jonathan P. Crall, Charles V. Stewart, Tanya Y. Berger-Wolf, Daniel I. Rubenstein:
Animal Population Censusing at Scale with Citizen Science and Photographic Identification. - Neetu Pathak, Michael J. Henry, Svitlana Volkova:
Understanding Social Media's Take on Climate Change through Large-Scale Analysis of Targeted Opinions and Emotions. - Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney:
Machine Representation of Data Analyses: Towards a Platform for Collaborative Data Science. - Mahendra Prasad:
Back to the Future: A Framework for Modelling Altruistic Intelligence Explosions. - Syed Ali Asad Rizvi, Elmarie van Heerden, Arnold Salas, Favour Nyikosa, Stephen J. Roberts, Michael A. Osborne, Elmer Rodriguez:
Identifying Sources of Discrimination Risk in the Life Cycle of Machine Intelligence Applications under New European Union Regulations. - Daniela Rosu, Dionne M. Aleman, J. Christopher Beck, Mark H. Chignell, Mariano P. Consens, Mark S. Fox, Michael Gruninger, Chang Liu, Yi Ru, Scott Sanner:
Knowledge-Based Provisioning of Goods and Services: Towards a Virtual Social Needs Marketplace. - Lanbo She, Jonathan Connell:
Teaching and Checking of Constraints for Surgical Tray Layout. - Jennifer Sleeman, Milton Halem, Tim Finin, Mark Cane:
Modeling the Evolution of Climate Change Assessment Research Using Dynamic Topic Models and Cross-Domain Divergence Maps. - Karen Judd Smith:
The AI Community and the United Nations: A Missing Global Conversation & A Closer Look at Social Good. - Yumeng Tao, Debarun Bhattacharjya, Aliza R. Heching, Aditya Vempaty, Moninder Singh, Felix Lam, Kush R. Varshney, Aleksandra Mojsilovic:
Statistical Analysis of Peer Detailing for Children's Diarrhea Treatments.
2 - Computational Construction Grammar and Natural Language Understanding
- James F. Allen, Choh Man Teng:
Broad Coverage, Domain-Generic Deep Semantic Parsing. - Michael A. Arbib, Nancy Chang, Peter F. Dominey, Victor Barrès, Michael Spranger:
Can We Already Conceive of a Computational Construction Grammar that is Adequate to Address the Data of Neurolinguistics? - Daphnée Azoulay:
Frame-Based Knowledge Representation Using Large Specialized Corpora. - Yulia Badryzlova, Olga Lyashevskaya:
Metaphor Shifts in Constructions: The Russian Metaphor Corpus. - Libby Barak, Adele E. Goldberg:
Modeling the Partial Productivity of Constructions. - Victor J. Barrès:
Template Construction Grammar: A Schema-Theoretic Computational Construction Grammar. - William Croft, Meagan Vigus:
Constructions, Frames and Event Structure. - Ellen Kirsten Dodge, Sean Trott, Luca Gilardi, Elise Stickles:
Grammar Scaling: Leveraging FrameNet Data to Increase Embodied Construction Grammar Coverage. - Peter Ford Dominey, Anne-Laure Mealier, Grégoire Pointeau, Solène Mirliaz, Mark A. Finlayson:
Dynamic Construction Grammar and Steps Towards the Narrative Construction of Meaning. - Steve Doubleday, Sean Trott, Jerome Feldman:
Processing Natural Language About Ongoing Actions in ECG. - Jesse Dunietz, Lori S. Levin, Miriam R. L. Petruck:
Construction Detection in a Conventional NLP Pipeline. - Denis Kiselev:
A Construction-Grammar Approach to Computationally Solving the Winograd Schema: Implementation and Evaluation. - Adrieli Laviola, Ludmila Lage, Natália Duarte Marção, Tatiane Tavares, Vânia Almeida, Ely Edison Matos, Tiago Torrent:
The Brazilian Portuguese Constructicon: Modeling Constructional Inheritance, Frame Evocation and Constraints in FrameNet Brasil. - Gianluca E. Lebani, Alessandro Lenci:
Modelling the Meaning of Argument Constructions with Distributional Semantics. - Timm Lichte, Laura Kallmeyer:
Tree-Adjoining Grammar: A Tree-Based Constructionist Grammar Framework for Natural Language Understanding. - Peter Lindes, John E. Laird:
Cognitive Modeling Approaches to Language Comprehension Using Construction Grammar. - Ely Edison Matos, Tiago Torrent, Vânia Almeida, Adrieli Laviola, Ludmila Lage, Natália Duarte Marção, Tatiane Tavares:
Constructional Analysis Using Constrained Spreading Activation in a FrameNet-Based Structured Connectionist Model. - Clifton James McFate, Kenneth D. Forbus:
A Proposal for Incorporating Analogically Learned Constructions in a Feature Based Parsing Framework. - Vivek Raghuram, Sean Trott, Kelly Shen, Ethan Goldberg, Sidney Oderberg:
Semantically-Driven Coreference Resolution with Embodied Construction Grammar. - Michael Spranger:
Usage-Based Grounded Construction Learning - A Computational Model. - Luc Steels:
Requirements for Computational Construction Grammars. - Paul Van Eecke, Katrien Beuls:
Meta-Layer Problem Solving for Computational Construction Grammar. - Remi van Trijp:
A Computational Construction Grammar for English. - Alexander Ziem, Hans C. Boas:
Towards a Constructicon for German.
3 - Computational Context: Why It's Important, What It Means, and Can It Be Computed?
- Olivier Bartheye, Laurent Chaudron:
Context Classification Using Entropy and Weak Negation: Some Criteria for Good Computational Properties. - R. Dirk Beer, Cory A. Rieth, Randy Tran, Maia B. Cook:
Framework for Multi-Human Multi-Robot Interaction: Impact of Operational Context and Team Configuration on Interaction Task Demands. - Beth Cardier:
The Moving Lens: Coherence Across Heterogeneous Contexts in Narrative and Biology. - Paul R. Cohen:
Context in Communication. - Laura Hiatt:
Computational Context as Cognitive Priming. - William Frere Lawless, Ranjeev Mittu, Donald A. Sofge:
(Computational) Context. Why It's Important, What It Means, Can It Be Computed? - Quan Liu, Hui Jiang, Zhen-Hua Ling, Xiaodan Zhu, Si Wei, Yu Hu:
Combing Context and Commonsense Knowledge Through Neural Networks for Solving Winograd Schema Problems. - Pujitha Mannaru, Balakumar Balasingam, Krishna R. Pattipati, Ciara Sibley, Joseph T. Coyne:
Heterogeneous Hidden Markov Models for Context Modeling Through Eye Gaze Observations. - Luke Marsh, Iryna Dzieciuch, Douglas Lange:
Machine Learning Approach for Task Generation in Uncertain Environments. - Manisha Mishra, David Sidoti, Gopi Vinod Avvari, Pujitha Mannaru, Diego Fernando Martinez Ayala, Krishna R. Pattipati:
Context-Driven Proactive Decision Support: Challenges and Applications. - Jeffrey G. Morrison:
Context Driven Decision Making in ONR's Command Decision Making Program (CDM). - Sergei Nirenburg, Marjorie J. McShane:
Contextual Knowledge for Language-Endowed Intelligent Agents. - Kristin E. Schaefer, Jessie Y. C. Chen, Julia L. Wright, Derya Aksaray, Nicholas Roy:
Challenges with Incorporating Context into Human-Robot Teaming. - Yotam Shmargad:
Network Perspectives on Privacy and Security in the Internet of Things: From Actor-Network Theory to Social Network Analysis. - Ciara Sibley:
Responsible Recommendations for Irrational People. - Michael Walton, Doug Lange, Song-Chun Zhu:
Inferring Context Through Scene Understanding. - Wayne Zachary, Taylor J. Carpenter
:
Cognitively-Inspired Computational Context.
4 - Designing the User Experience of Machine Learning Systems
- Francisco Bernardo, Michael Zbyszynski, Rebecca Fiebrink, Mick Grierson:
Interactive Machine Learning for End-User Innovation. - Fabien Girardin, Neal Lathia:
When User Experience Designers Partner with Data Scientists. - Chieh-Yang Huang, Ting-Hao Kenneth Huang, Lun-Wei Ku:
Challenges in Providing Automatic Affective Feedback in Instant Messaging Applications. - Ranjitha Kumar, Kristen Vaccaro:
An Experimentation Engine for Data-Driven Fashion Systems. - Jacobus Cornelius Lock, Grzegorz Cielniak, Nicola Bellotto:
A Portable Navigation System with an Adaptive Multimodal Interface for the Blind. - Narayanan Seshadri, Gyanit Singh, Justin House, Mukesh Nathan, Nish Parikh:
Communicating Machine Learned Choices to E-Commerce Users. - Qian Yang:
The Role of Design in Creating Machine-Learning-Enhanced User Experience. - Henriette Cramer, Jennifer Thom:
Not-so-Autonomous, Very Human Decisions in Machine Learning: Questions When Designing for ML. - Janin Koch:
Design implications for Designing with a Collaborative AI. - Nikolas Martelaro, Wendy Ju:
DJ Bot: Needfinding Machines for Improved Music Recommendations. - Vidya Setlur, Melanie Tory:
Exploring Synergies between Visual Analytical Flow and Language Pragmatics. - Aaron Springer, Victoria Hollis, Steve Whittaker:
Dice in the Black Box: User Experiences with an Inscrutable Algorithm. - Philip van Allen:
Reimagining the Goals and Methods of UX for ML/AI. - Joël van Bodegraven:
How Anticipatory Design Will Challenge Our Relationship with Technology. - Jonathan Vitale, Meg Tonkin, Suman Ojha, Mary-Anne Williams, Xun Wang, William Judge:
Privacy by Design in Machine Learning Data Collection: A User Experience Experimentation.
5 - Interactive Multisensory Object Perception for Embodied Agents
- Muhannad Al-Omari, Paul Duckworth, David C. Hogg, Anthony G. Cohn:
Learning of Object Properties, Spatial Relations, and Actions for Embodied Agents from Language and Vision. - Alex Burka, Katherine J. Kuchenbecker:
How Much Haptic Surface Data Is Enough? - Yevgen Chebotar, Karol Hausman, Oliver Kroemer, Gaurav S. Sukhatme, Stefan Schaal:
Regrasping Using Tactile Perception and Supervised Policy Learning. - Rebecca Cox, Nikolaus Correll:
Merging Local and Global 3D Perception using Contact Sensing. - Scott Michael Jordan, Dirk Ruiken, Tiffany Q. Liu, Takeshi Takahashi, Michael William Lanighan, Roderic A. Grupen:
Summary of Experiments in Belief-Space Planning at the Laboratory for Perceptual Robotics. - Wenbin Li, Ales Leonardis, Mario Fritz:
Visual Stability Prediction and Its Application to Manipulation. - Roberto Martín-Martín, Oliver Brock:
Building Kinematic and Dynamic Models of Articulated Objects with Multi-Modal Interactive Perception. - Kory W. Mathewson, Patrick M. Pilarski:
Reinforcement Learning Based Embodied Agents Modelling Human Users Through Interaction and Multi-Sensory Perception. - German Ignacio Parisi, Pablo V. A. Barros, Haiyan Wu, Guochun Yang, Zhenghan Li, Xun Liu, Stefan Wermter:
A Deep Neural Model for Emotion-Driven Multimodal Attention.
6 - Learning from Observation of Humans
- Mihai Sorin Dobre, Alex Lascarides:
Combining a Mixture of Experts with Transfer Learning in Complex Games. - Michael W. Floyd, J. T. Turner, David W. Aha:
Using Deep Learning to Automate Feature Modeling in Learning by Observation: A Preliminary Study. - Amrik Sacha Elapata Gunaratne, Babak Esfandiari, Caleb Chan:
Towards a Framework for Testing Learning from Observation of State-Based Agents. - Santiago Ontañón, Yi-Ching Lee, Sam Snodgrass, Flaura K. Winston, Avelino J. Gonzalez:
Learning to Predict Driver Behavior from Observation. - Brandon Packard, Santiago Ontañón:
Policies for Active Learning from Demonstration. - Cristina Tîrnauca, José Luis Montaña, Zoraida Mediavilla:
Neural Networks in Autonomous Driving.
7 - Science of Intelligence: Computational Principles of Natural and Artificial Intelligence
- Guy Ben-Yosef, Alon Yachin, Shimon Ullman:
A Model for Interpreting Social Interactions in Local Image Regions. - Jeremy Bernstein, Ishita Dasgupta, David Rolnick, Haim Sompolinsky:
Markov Transitions between Attractor States in a Recurrent Neural Network. - Beth Cardier, Larry D. Sanford, H. Ted Goranson, Patric S. Lundberg, Richard P. Ciavarra, Keith Devlin, Niccolo Cassas, Alessio Erioli:
Modeling the Resituation of Memory in Neurobiology and Narrative. - Francis X. Chen, Gemma Roig, Leyla Isik, Xavier Boix, Tomaso A. Poggio:
Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision. - Yansong Chua, Cheston Tan:
Multiple Plasticity Mechanisms Enhance Associative Memory Retrieval in a Spiking Network Model of the Hippocampus. - Ana Garcia del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan:
On Active Video Summarization: Customized Summaries via On-Line Interaction with the User. - Leilani Hendrina Gilpin, Ben Ze Yuan:
Getting Up to Speed on Vehicle Intelligence. - Yena Han, Gemma Roig, Gadi Geiger, Tomaso A. Poggio:
Is the Human Visual System Invariant to Translation and Scale? - Seng-Beng Ho:
Principles of Noology: A Theory and Science of Intelligence for Natural and Artificial Intelligence. - Wentao Huang, Kai Liu:
Unsupervised Learning via Maximizing Mutual Information in Neural Population Coding. - Seyed-Mahdi Khaligh-Razavi, Radoslaw Martin Cichy, Dimitrios Pantazis, Aude Oliva:
Content-Dependent Fusion: Combining Human MEG and FMRI Data to Reveal Spatiotemporal Dynamics of Animacy and Real-world Object Size. - Pavitra Krishnaswamy, Gabriel Obregon-Henao, Sheraz Khan, Behtash Babadi, Eugenio Iglesias, Matti S. Hämäläinen, Patrick L. Purdon:
Sparse Representation Learning Approach Resolves Deep Sources Underlying MEG and EEG Data. - Eric Laukien, Richard Crowder, Fergal Byrne:
Feynman Machine: A Novel Neural Architecture for Cortical and Machine Intelligence. - Robert Lew, Hongsheng Wu, Chen-Hsiang Yu:
Integrating Human Input for Decision Making with Informative Bayesian Beliefs. - Melanie Mitchell:
Active Interpretation of Visual Situations. - Olivier Morère, Antoine Veillard, Jie Lin, Julie Petta, Vijay Chandrasekhar, Tomaso A. Poggio:
Group Invariant Deep Representations for Image Instance Retrieval. - German Ignacio Parisi, Stefan Wermter:
Lifelong Learning of Action Representations with Deep Neural Self-Organization. - Dimitris A. Pinotsis, Earl K. Miller:
New Approaches for Studying Cortical Representations. - Mona Ragab Sayed, Rosary Yuting Lim, Bappaditya Mandal, Liyuan Li, Joo-Hwee Lim, Terence Sim:
Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance. - Camilo Miguel Signorelli:
Types of Cognition and Its Implications for Future High-Level Cognitive Machines. - Andrea Tacchetti, Stephen Voinea, Georgios Evangelopoulos, Tomaso A. Poggio:
Representation Learning from Orbit Sets for One-Shot Classification. - Zenna Tavares, Armando Solar-Lezama:
Mental Representations as Distribution-Sensitive Data Structures. - Zoran Tiganj, Karthik H. Shankar, Marc W. Howard:
Scale Invariant Value Computation for Reinforcement Learning in Continuous Time. - Pedro Tsividis, Thomas Pouncy, Jaqueline L. Xu, Joshua B. Tenenbaum, Samuel J. Gershman:
Human Learning in Atari. - Alessia Vignolo, Alessandra Sciutti, Francesco Rea, Nicoletta Noceti, Francesca Odone, Giulio Sandini:
Computational Vision for Social Intelligence. - Anna Volokitin, Michael Gygli, Xavier Boix:
Predicting When Eye Fixations Are Consistent.
8 - Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing
- Nicola Bellotto, Manuel Fernández-Carmona, Serhan Cosar:
ENRICHME Integration of Ambient Intelligence and Robotics for AAL. - Tomohiro Harada, Takahiro Kawashima, Morito Morishima, Keiki Takadama:
Improving Accuracy of Real-Time Sleep Stage Estimation by Considering Personal Sleep Feature and Rapid Change of Sleep Behavior. - Takayoshi Hayashi:
Research and Development Trend Analysis of Wellbeing AI Using Panoramic View Analytics. - Tomoyuki Hiroyasu, Satoru Hiwa:
Brain Functional State Analysis of Mindfulness Using Graph Theory and Functional Connectivity. - Masafumi Ishii, Jinhwan Kwon, Keiki Takadama, Maki Sakamoto:
Visual Impression Generation System Based on Boids Algorithm. - Tabito Kurosaka, Mihoko Otake:
The Robot Facilitating Conversation by Revoicing Keywords Learning from Active Conversations among Healthy Old Sisters. - Jinhwan Kwon, Xiaoqian Fang, Yoshihiro Miyake:
The Role of Body Motion Synchrony in Distance Education. - Shuya Masuda, Masayuki Numao:
Sensor-Based Detection of Invisible Changes in Activities towards Visualizing Disuse Syndrome. - Tatsuo Nakamura:
How Do Huge M&As Affect Our Health? - Shweta Oak:
Depression Detection and Analysis. - Hikaru Otaki, Mihoko Otake:
Interactive Robotic System Assisting Image Based Dialogue for the Purpose of Cognitive Training of Older Adults. - Pujana Paliyawan, Takahiro Kusano, Yuto Nakagawa, Tomohiro Harada, Ruck Thawonmas:
Adaptive Motion Gaming AI for Health Promotion. - Camille Ruiz, Kaoru Ito, Shoko Wakamiya, Eiji Aramaki:
Loneliness in a Connected World: Analyzing Online Activity and Expressions on Real Life Relationships of Lonely Users. - Yusuke Tajima, Tomohiro Harada, Keiki Takadama:
Sleep Stage Estimation Based on Appriximate Heartrate Calculated from Other Persons. - Keiki Takadama:
Towards Guideline for Applying Machine Learning into Care Support Systems. - Madoka Takahara, Fangwei Huang, Ivan Tanev, Katsunori Shimohara:
Mutual Awareness beyond Mutual Acceptance by Sharing Information through Indirect Biofeedback. - Takashi Kido, Keiki Takadama:
Wellbeing AI Invited Speaker Abstracts.
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