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Friday
, December 11
08:30 EST
ABC in Montreal
511 a
Adaptive Data Analysis
514 a
Advances in Approximate Bayesian Inference
513 ab
Applying (machine) Learning to Experimental Physics (ALEPH) and «Flavours of Physics» challenge
515 bc
Bounded Optimality and Rational Metareasoning
512 bf
Cognitive Computation: Integrating neural and symbolic approaches
512 cg
Deep Reinforcement Learning
513 cd
Learning Faster from Easy Data II
511 d
Machine Learning and Interpretation in Neuroimaging (day 1)
Room 515 a
Machine Learning for (e-)Commerce
512 e
Machine Learning For Healthcare (MLHC)
510 db
Machine Learning for Spoken Language Understanding and Interactions
511 b
Modelling and inference for dynamics on complex interaction networks: joining up machine learning and statistical physics
511 e
Multimodal Machine Learning
512 dh
Nonparametric Methods for Large Scale Representation Learning
511 c
Optimization for Machine Learning (OPT2015)
510 ac
Probabilistic Integration
512 a
Statistical Methods for Understanding Neural Systems
511 f
The 1st International Workshop 'Feature Extraction: Modern Questions and Challenges'
513 ef
Time Series Workshop
514 bc
Saturday
, December 12
08:00 EST
Extreme Classification 2015: Multi-class and Multi-label Learning in Extremely Large Label Spaces
511 f
08:30 EST
Bayesian Nonparametrics: The Next Generation
515 bc
Bayesian Optimization: Scalability and Flexibility
511 b
BigNeuro 2015: Making sense of big neural data
511 e
Black box learning and inference
513 ef
Challenges in Machine Learning (CiML 2015): 'Open Innovation' and 'Coopetitions'
512 e
Learning and privacy with incomplete data and weak supervision
512 dh
Learning, Inference and Control of Multi-Agent Systems
511 a
Machine Learning From and For Adaptive User Technologies: From Active Learning & Experimentation to Optimization & Personalization
514 a
Machine Learning in Computational Biology
510 db
Machine Learning Systems
511 d
Multiresolution methods for large-scale learning
511 c
Networks in the Social and Information Sciences
512 bf
Non-convex Optimization for Machine Learning: Theory and Practice
513 cd
Quantum Machine Learning
512 a
Reasoning, Attention, Memory (RAM) Workshop
510 ac
Scalable Monte Carlo Methods for Bayesian Analysis of Big Data
513 ab
Transfer and Multi-Task Learning: Trends and New Perspectives
514 bc
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NIPS 2015
Dec 7
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12, 2015
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210
210 A
210 a,b Level 2
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210 e, f Level 2
210D
220 A
220A
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511 a
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511 d
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511 f
512 a
512 bf
512 cg
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Foyer - 5th floor
Level 2 room 210 AB
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Level 5 Room 510 BD
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Monday
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, December 11
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, December 12
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210
210 A
210 a,b Level 2
210 C
210 C #1
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210 C #5
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210 C #51
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210 e, f Level 2
210D
220 A
220A
510 ac
510 db
511 a
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511 c
511 d
511 e
511 f
512 a
512 bf
512 cg
512 dh
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513 ab
513 cd
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514 bc
515 bc
Foyer - 5th floor
Level 2 room 210 AB
Level 2 room 210 E,F
Level 5 Room 510 BD
Room 210 A
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