Timezone: America/Montreal »
Indicates the beginning of a sessionMon Dec 07, 2015  
Time  Level 2 room 210 AB  210 C #20  210 C #18  210 C #24  210 C #98  210 C #81  210 C #34  210 C #71  210 C #46  210 C #85  210 C #54  210 C #3  210 C #94  210 C #83  210 C #51  210 C #62  210 C #58  210 C #8  210 C #21  210 C #10  210 C #97  210 C #95  210 C #13  210 C #61  210 C #15  210 C #11  210 C #100  210 C #68  210 C #66  210 C #76  210 C #57  210 C #48  210 C #14  210 C #52  210 C #28  210 C #26  210 C #40  210 C #43  210 C #42  210 C #4  210 C #37  210 C #45  210 C #80  210 C #82  210 C #6  210 C #49  210 C #30  210 C #87  210 C #1  210 C #78  210 C #96  210 C #12  210 C #102  210 C #70  210 C #22  210 C #39  210 C #101  210 C #89  210 C #77  210 C #75  210 C #84  210 C #67  210 C #25  210 C #19  210 C #32  210 C #2  210 C #7  210 C #29  210 C #72  210 C #59  210 C #60  210 C #38  210 C #33  210 C #63  210 C #90  210 C #50  210 C #88  210 C #92  210 C #56  210 C #35  210 C #99  210 C #55  210 C #16  210 C #5  210 C #73  210 C #41  210 C #53  210 C #69  210 C #47  210 C #91  210 C #65  210 C #36  210 C #74  210 C #44  210 C #79  210 C #64  210 C #9  210 C #31  210 C #27  210 C #17  210 C #93  210 C #23  Level 2 room 210 E,F  220 A 

09:30 AM (Tutorials)  
11:00 AM (Breaks)  
01:00 PM (Tutorials)  
03:30 PM (Tutorials)  
07:00 PM (Posters) 
Minimax Time Series Prediction
210 C #98

Grammar as a Foreign Language
210 C #3

Learning with Relaxed Supervision
210 C #51

Nearly Optimal Private LASSO
210 C #97

The Poisson Gamma Belief Network
210 C #13

Decomposition Bounds for Marginal MAP
210 C #68

Discrete RÃ©nyi Classifiers
210 C #66

Calibrated Structured Prediction
210 C #26

Expectation Particle Belief Propagation
210 C #42

Copula variational inference
210 C #37

Robust Portfolio Optimization
210 C #82

Deep Knowledge Tracing
210 C #22

Combinatorial Cascading Bandits
210 C #90

Halting in Random Walk Kernels
210 C #56

Infinite Factorial Dynamical Model
210 C #35

Regressive Virtual Metric Learning
210 C #55

Robust PCA with compressed data
210 C #73

Learning with a Wasserstein Loss
210 C #47

StopWasting My Gradients: Practical SVRG
210 C #79

Online Gradient Boosting
210 C #93

Tue Dec 08, 2015  
Time  210D  Level 2 room 210 AB  Room 210 AB  Room 210 A  210 C #20  210 C #18  210 C #24  210 C #98  210 C #81  210 C #34  210 C #71  210 C #46  210 C #85  210 C #54  210 C #3  210 C #94  210 C #83  210 C #51  210 C #58  210 C #8  210 C #21  210 C #10  210 C #97  210 C #95  210 C #13  210 C #61  210 C #15  210 C #11  210 C #100  210 C #68  210 C #66  210 C #76  210 C #57  210 C #48  210 C #14  210 C #52  210 C #28  210 C #26  210 C #40  210 C #43  210 C #42  210 C #4  210 C #37  210 C #45  210 C #80  210 C #82  210 C #6  210 C #49  210 C #30  210 C #87  210 C #1  210 C #78  210 C #96  210 C #12  210 C #70  210 C #22  210 C #39  210 C #101  210 C #89  210 C #77  210 C #75  210 C #84  210 C #67  210 C #25  210 C #19  210 C #32  210 C #2  210 C #7  210 C #29  210 C #72  210 C #59  210 C #60  210 C #38  210 C #33  210 C #63  210 C #90  210 C #50  210 C #88  210 C #86  210 C #92  210 C #56  210 C #35  210 C #99  210 C #55  210 C #16  210 C #5  210 C #73  210 C #41  210 C #53  210 C #69  210 C #47  210 C #91  210 C #65  210 C #36  210 C #74  210 C #44  210 C #79  210 C #64  210 C #9  210 C #31  210 C #27  210 C #17  210 C #93  210 C #23 

09:00 AM (Invited Talks)  
09:50 AM (Orals)  
10:10 AM (Spotlights)  
10:55 AM (Orals)  
11:35 AM (Spotlights)  
02:00 PM (Invited Talks)  
02:50 PM (Orals)  
03:30 PM (Spotlights)  
04:30 PM (Orals)  
05:30 PM (Spotlights)  
07:00 PM (Demonstrations, Posters) 
Tensorizing Neural Networks
210 C #18

The Human Kernel
210 C #24

On Elicitation Complexity
210 C #98

bbit Marginal Regression
210 C #81

Automatic Variational Inference in Stan
210 C #34

Submodular Hamming Metrics
210 C #71

SuperResolution Off the Grid
210 C #94

Policy Evaluation Using the Î©Return
210 C #51

Topk Multiclass SVM
210 C #61

WinnerTakeAll Autoencoders
210 C #11

Deep learning with Elastic Averaging SGD
210 C #37

Subset Selection by Pareto Optimization
210 C #78

Combinatorial Bandits Revisited
210 C #96

Online Learning with Adversarial Delays
210 C #99

Deep Poisson Factor Modeling
210 C #16

Stochastic Expectation Propagation
210 C #36

Wed Dec 09, 2015  
Time  210D  Level 2 room 210 AB  Room 210 A  210 C #20  210 C #18  210 C #24  210 C #98  210 C #81  210 C #34  210 C #71  210 C #46  210 C #85  210 C #54  210 C #3  210 C #94  210 C #83  210 C #51  210 C #62  210 C #58  210 C #8  210 C #21  210 C #10  210 C #97  210 C #95  210 C #13  210 C #61  210 C #15  210 C #11  210 C #100  210 C #68  210 C #66  210 C #76  210 C #57  210 C #48  210 C #14  210 C #52  210 C #28  210 C #26  210 C #40  210 C #43  210 C #42  210 C #4  210 C #37  210 C #45  210 C #80  210 C #82  210 C #6  210 C #49  210 C #30  210 C #87  210 C #1  210 C #78  210 C #96  210 C #12  210 C #70  210 C #22  210 C #39  210 C #89  210 C #77  210 C #75  210 C #84  210 C #67  210 C #25  210 C #19  210 C #32  210 C #2  210 C #7  210 C #29  210 C #72  210 C #59  210 C #60  210 C #38  210 C #33  210 C #63  210 C #90  210 C #50  210 C #88  210 C #86  210 C #92  210 C #56  210 C #35  210 C #99  210 C #55  210 C #16  210 C #5  210 C #73  210 C #41  210 C #53  210 C #69  210 C #47  210 C #91  210 C #65  210 C #36  210 C #74  210 C #44  210 C #79  210 C #64  210 C #9  210 C #31  210 C #27  210 C #17  210 C #93  210 C #23  220 A 

09:00 AM (Invited Talks)  
09:50 AM (Orals)  
10:10 AM (Spotlights)  
10:30 AM (Breaks)  
10:55 AM (Orals)  
11:35 AM (Spotlights)  
02:00 PM (Invited Talks)  
02:50 PM (Orals)  
03:30 PM (Spotlights)  
04:30 PM (Invited Talks)  
05:20 PM (Orals)  
05:40 PM (Spotlights) 