Joseph Modayil - Citegraph

Author Info

Name	Affiliation	Papers
JOSEPH MODAYIL	Department of Computer Science, University of Rochester,PO Box 270226 734 Computer Studies Bldg. Rochester, NY, USA, 14627-0226	28
Collaborators	Citations	PageRank
65	403	29.02
Referers	Referees	References
1116	527	303

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Publications (28 rows)

Collaborators (65 rows)

Referers (100 rows)

Referees (100 rows)

Title	Citations	PageRank	Year
Ray Interference: a Source of Plateaus in Deep Reinforcement Learning.	0	0.34	2019
Deep Reinforcement Learning and the Deadly Triad.	2	0.37	2018
The Barbados 2018 List of Open Issues in Continual Learning.	0	0.34	2018
Rainbow: Combining Improvements in Deep Reinforcement Learning.	66	1.89	2018
Natural Value Approximators: Learning when to Trust Past Estimates.	0	0.34	2017
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017.	2	0.39	2017
Universal Option Models.	6	0.61	2014
Two Perspectives on Learning Rich Representations from Robot Experience.	0	0.34	2013
Acquiring a broad range of empirical knowledge in real time by temporal-difference learning	4	0.50	2012
Scaling-up Knowledge for a Cognizant Robot.	5	0.50	2012
Multi-timescale nexting in a reinforcement learning robot	18	1.22	2011
Horde: a scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction	24	2.44	2011
Factoring the Mapping Problem: Mobile Robot Map-building in the Hybrid Spatial Semantic Hierarchy	41	1.45	2010
Learning Grounded Communicative Intent from Human-Robot Dialog.	0	0.34	2010
Discovering sensor space: Constructing spatial embeddings that explain sensor correlations	7	0.58	2010
The Initial Development of Object Knowledge by a Learning Robot.	24	1.13	2008
Integrating Sensing and Cueing for More Effective Activity Reminders	15	1.06	2008
Improving the recognition of interleaved activities	46	1.95	2008
Where Do Actions Come From? Autonomous Robot Learning of Objects and Actions.	2	0.41	2007
Integrating Multiple Representations of Spatial Knowledge for Mapping, Navigation, and Communication.	13	0.88	2007
Autonomous development of a grounded object ontology by a learning robot	17	1.00	2007
Autonomous Shape Model Learning For Object Localization And Recognition	7	0.55	2006
Building Local Safety Maps for a Wheelchair Robot using Vision and Lasers	12	1.17	2006
Bootstrap Learning Of Foundational Representations	28	1.97	2006
Bootstrap Learning for Object Discovery	36	2.74	2004
Using the topological skeleton for scalable global metrical map-building	24	1.87	2004
An improved piecewise approximation algorithm for image compression	1	1.12	1998
Experiments in Simple One-Dimensional Lossy Image Compression Schemes	3	1.52	1997