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Dec. 2, 2018 Expo schedule » New in ML »

Timezone: America/Montreal »

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Time	Room 220 CD	Room 517 CD	Room 220 E
Mon Dec 03, 2018
08:30 AM (Tutorials)	Adversarial Robustness: Theory and Practice	Scalable Bayesian Inference	Visualization for Machine Learning
11:00 AM (Tutorials)	Unsupervised Deep Learning	Negative Dependence, Stable Polynomials, and All That	Tutorials Session 2 Common Pitfalls for Studying the Human Side of Machine Learning
02:30 PM (Tutorials)	Automatic Machine Learning	Counterfactual Inference	Statistical Learning Theory: a Hitchhiker's Guide
05:30 PM (Invited Talks)	Accountability and Algorithmic Bias: Why Diversity and Inclusion Matters

Time	Room 210	Room 220 CD	Room 517 CD	Room 220 E	Room 510 ABCD #D10	Room 510 ABCD #D7	Room 510 ABCD #D1	Room 510 ABCD #D5	Room 510 ABCD #D9	Room 510	Room 510 ABCD #D4	Room 510 ABCD #D8	Room 510 ABCD #D3	Room 517 AB
Tue Dec 04, 2018
08:30 AM (Invited Talks)		Tue Invited Talk 1 Machine Learning Meets Public Policy: What to Expect and How to Cope
10:05 AM (Orals)		Tue Track 1 -- Session 1 On Neuronal Capacity	Tue Track 3 -- Session 1 Phase Retrieval Under a Generative Prior	Tue Track 2 -- Session 1 On the Dimensionality of Word Embedding
10:20 AM (Spotlights)		Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data	Global Geometry of Multichannel Sparse Blind Deconvolution on the Sphere	Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces
10:25 AM (Spotlights)		Size-Noise Tradeoffs in Generative Networks	Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds	Diffusion Maps for Textual Network Embedding
10:30 AM (Orals)		Dendritic cortical microcircuits approximate the backpropagation algorithm	Spectral Filtering for General Linear Dynamical Systems	A Retrieve-and-Edit Framework for Predicting Structured Outputs
10:45 AM (Demonstrations, Posters)	Tue Poster Session A				TextWorld: A Learning Environment for Text-based Games	A Hands-free Natural User Interface (NUI) for AR/VR Head-Mounted Displays Exploiting Wearer’s Facial Gestures	Tue Demonstrations Deep Neural Networks Running Onboard Anki’s Robot, Vector	Deep learning to improve quality control in pharmaceutical manufacturing	A machine learning environment to determine novel malaria policies	Reproducing Machine Learning Research on Binder TensorFlow Dance - Learning to Dance via Machine Learning	Game for Detecting Backdoor Attacks on Deep Neural Networks using Activation Clustering	A model-agnostic web interface for interactive music composition by inpainting	Ruuh: A Deep Learning Based Conversational Social Agent	Tue Poster Session A
02:15 PM (Invited Talks)		Tue Invited Talk 2 What Bodies Think About: Bioelectric Computation Outside the Nervous System, Primitive Cognition, and Synthetic Morphology
03:30 PM (Spotlights)		Tue Track 1 -- Session 2 Neural Voice Cloning with a Few Samples	Tue Track 3 -- Session 2 Differentially Private Testing of Identity and Closeness of Discrete Distributions	Tue Track 2 -- Session 2 Evolved Policy Gradients
03:35 PM (Spotlights)		Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog	Local Differential Privacy for Evolving Data	Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning
03:40 PM (Spotlights)		Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding	Differentially Private k-Means with Constant Multiplicative Error	Bayesian Model-Agnostic Meta-Learning
03:45 PM (Spotlights)		Learning to Optimize Tensor Programs	A Spectral View of Adversarially Robust Features	Probabilistic Neural Programmed Networks for Scene Generation
03:50 PM (Orals)		Generalisation of structural knowledge in the hippocampal-entorhinal system	Model-Agnostic Private Learning	Neural Ordinary Differential Equations
04:05 PM (Spotlights)		A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks	Bounded-Loss Private Prediction Markets	Bias and Generalization in Deep Generative Models: An Empirical Study
04:10 PM (Spotlights)		Generalizing Tree Probability Estimation via Bayesian Networks	cpSGD: Communication-efficient and differentially-private distributed SGD	Robustness of conditional GANs to noisy labels
04:15 PM (Breaks, Spotlights)		Geometry Based Data Generation	Inclusion and Diversity Town Hall Adversarially Robust Generalization Requires More Data	BourGAN: Generative Networks with Metric Embeddings
04:20 PM (Spotlights)		Point process latent variable models of larval zebrafish behavior	Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples	Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
04:25 PM (Orals)		A probabilistic population code based on neural samples	Learning to Solve SMT Formulas	How Does Batch Normalization Help Optimization?
04:40 PM (Spotlights)		Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding	Towards Robust Detection of Adversarial Examples	Training Neural Networks Using Features Replay
04:45 PM (Spotlights)		Learning Temporal Point Processes via Reinforcement Learning	Neural Architecture Search with Bayesian Optimisation and Optimal Transport	Step Size Matters in Deep Learning
04:50 PM (Spotlights)		Precision and Recall for Time Series	Data-Driven Clustering via Parameterized Lloyd's Families	Neural Tangent Kernel: Convergence and Generalization in Neural Networks
04:55 PM (Spotlights)		Bayesian Nonparametric Spectral Estimation	Supervising Unsupervised Learning	Hierarchical Graph Representation Learning with Differentiable Pooling
05:00 PM (Posters)	Tue Poster Session B													Tue Poster Session B

Time	Room 210	Room 220 CD	Room 517 CD	Room 220 E	Room 510 ABCD #D10	Room 510 ABCD #D7	Room 510 ABCD #D1	Room 510 ABCD #D9	Room 510	Room 510 ABCD #D4	Room 510 ABCD #D8	Room 510 ABCD #D3	Room 510 ABCD #D6	Room 517 AB
Wed Dec 05, 2018
08:30 AM (Invited Talks)		Wed Invited Talk 1 Reproducible, Reusable, and Robust Reinforcement Learning
09:45 AM (Spotlights)		Wed Track 1 -- Session 1 A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem	Wed Track 3 -- Session 1 Revisiting $(\epsilon, \gamma, \tau)$-similarity learning for domain adaptation	Wed Track 2 -- Session 1 Deep Network for the Integrated 3D Sensing of Multiple People in Natural Images
09:50 AM (Spotlights)		Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs	Leveraged volume sampling for linear regression	Delta-encoder: an effective sample synthesis method for few-shot object recognition
09:55 AM (Spotlights)		End-to-End Differentiable Physics for Learning and Control	Synthesize Policies for Transfer and Adaptation across Tasks and Environments	Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
10:00 AM (Spotlights)		Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes	Sublinear Time Low-Rank Approximation of Distance Matrices	Neighbourhood Consensus Networks
10:05 AM (Orals)		Exploration in Structured Reinforcement Learning	Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes	Visual Memory for Robust Path Following
10:20 AM (Spotlights)		Acceleration through Optimistic No-Regret Dynamics	Minimax Statistical Learning with Wasserstein distances	Recurrent Transformer Networks for Semantic Correspondence
10:25 AM (Spotlights)		On Oracle-Efficient PAC RL with Rich Observations	Generalization Bounds for Uniformly Stable Algorithms	Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
10:30 AM (Spotlights)		Constant Regret, Generalized Mixability, and Mirror Descent	A loss framework for calibrated anomaly detection	Sanity Checks for Saliency Maps
10:35 AM (Spotlights)		Efficient Online Portfolio with Logarithmic Regret	Sharp Bounds for Generalized Uniformity Testing	A Probabilistic U-Net for Segmentation of Ambiguous Images
10:40 AM (Spotlights)		Solving Large Sequential Games with the Excessive Gap Technique	Convex Elicitation of Continuous Properties	Virtual Class Enhanced Discriminative Embedding Learning
10:45 AM (Demonstrations, Posters)	Wed Poster Session A				Automatic Curriculum Generation Applied to Teaching Novices a Short Bach Piano Segment	Wed Demonstrations Multi-Word Imputation and Sentence Expansion	BigBlueBot: A Demonstration of How to Detect Egregious Conversations with Chatbots	A Cooperative Visually Grounded Dialogue Game with a Humanoid Robot	PatentAI: IP Infringement Detection with Enhanced Paraphrase Identification Perception, sensing, motion planning and robot control using AI for automated feeding of upper-extremity mobility impaired people	RieszNets: Accurate Real-Time 2D/3D Image Super-Resolution	Autonomous robotic manipulation with a desktop research platform	Wed Demonstrations Play Imperfect Information Games against Neural Networks	Wed Demonstrations Deep Reinforcement Learning for Online Order Dispatching and Driver Repositioning in Ride-sharing	Wed Poster Session A
02:15 PM (Invited Talks)		Wed Invited Talk 2 Investigations into the Human-AI Trust Phenomenon
03:30 PM (Spotlights)		Wed Track 1 -- Session 2 Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation	Wed Track 3 -- Session 2 The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal	Wed Track 2 -- Session 2 Dynamic Network Model from Partial Observations
03:35 PM (Spotlights)		Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation	Contextual Stochastic Block Models	Stochastic Nonparametric Event-Tensor Decomposition
03:40 PM (Spotlights)		Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing	Entropy Rate Estimation for Markov Chains with Large State Space	On GANs and GMMs
03:45 PM (Spotlights)		Meta-Reinforcement Learning of Structured Exploration Strategies	Blind Deconvolutional Phase Retrieval via Convex Programming	GILBO: One Metric to Measure Them All
03:50 PM (Orals)		Policy Optimization via Importance Sampling	Stochastic Cubic Regularization for Fast Nonconvex Optimization	Isolating Sources of Disentanglement in Variational Autoencoders
04:05 PM (Spotlights)		A Bayesian Approach to Generative Adversarial Imitation Learning	Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization
04:10 PM (Spotlights)		Visual Reinforcement Learning with Imagined Goals	On the Local Minima of the Empirical Risk	Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features
04:15 PM (Spotlights)		Randomized Prior Functions for Deep Reinforcement Learning	How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?	Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
04:20 PM (Spotlights)		Playing hard exploration games by watching YouTube	SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator	Adversarially Robust Optimization with Gaussian Processes
04:25 PM (Orals)		Recurrent World Models Facilitate Policy Evolution	Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems	Approximate Knowledge Compilation by Online Collapsed Importance Sampling
04:40 PM (Spotlights)		Reducing Network Agnostophobia	Natasha 2: Faster Non-Convex Optimization Than SGD	DAGs with NO TEARS: Continuous Optimization for Structure Learning
04:45 PM (Spotlights)		Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies	Escaping Saddle Points in Constrained Optimization	Proximal Graphical Event Models
04:50 PM (Spotlights)		Geometrically Coupled Monte Carlo Sampling	On Coresets for Logistic Regression	Heterogeneous Multi-output Gaussian Process Prediction
04:55 PM (Spotlights)		Scalable Laplacian K-modes	Legendre Decomposition for Tensors	GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
05:00 PM (Posters)	Wed Poster Session B													Wed Poster Session B

Time	Room 210	Room 220 CD	Room 517 CD	Room 220 E	Room 517 AB
Thu Dec 06, 2018
08:30 AM (Invited Talks)		Thu Invited Talk 1 Making Algorithms Trustworthy: What Can Statistical Science Contribute to Transparency, Explanation and Validation?
09:45 AM (Spotlights)		Thu Track 1 -- Session 1 Learning with SGD and Random Features	Thu Track 3 -- Session 1 Boolean Decision Rules via Column Generation	Thu Track 2 -- Session 1 Graphical model inference: Sequential Monte Carlo meets deterministic approximations
09:50 AM (Spotlights)		KONG: Kernels for ordered-neighborhood graphs	Fast greedy algorithms for dictionary selection with generalized sparsity constraints	Boosting Black Box Variational Inference
09:55 AM (Spotlights)		Quadrature-based features for kernel approximation	Distributed $k$-Clustering for Data with Heavy Noise	Discretely Relaxing Continuous Variables for tractable Variational Inference
10:00 AM (Spotlights)		Statistical and Computational Trade-Offs in Kernel K-Means	Do Less, Get More: Streaming Submodular Maximization with Subsampling	Implicit Reparameterization Gradients
10:05 AM (Orals)		Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models	Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization	Variational Inference with Tail-adaptive f-Divergence
10:20 AM (Spotlights)		Why Is My Classifier Discriminatory?	Overlapping Clustering Models, and One (class) SVM to Bind Them All	Mirrored Langevin Dynamics
10:25 AM (Spotlights)		Human-in-the-Loop Interpretability Prior	Removing the Feature Correlation Effect of Multiplicative Noise	Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
10:30 AM (Spotlights)		Link Prediction Based on Graph Neural Networks	Connectionist Temporal Classification with Maximum Entropy Regularization	Identification and Estimation of Causal Effects from Dependent Data
10:35 AM (Spotlights)		Realistic Evaluation of Deep Semi-Supervised Learning Algorithms	Entropy and mutual information in models of deep neural networks	Causal Inference via Kernel Deviance Measures
10:40 AM (Spotlights)		Automatic differentiation in ML: Where we are and where we should be going	The committee machine: Computational to statistical gaps in learning a two-layers neural network	Removing Hidden Confounding by Experimental Grounding
10:45 AM (Posters)	Thu Poster Session A				Thu Poster Session A
02:15 PM (Invited Talks)		Thu Invited Talk 2 Designing Computer Systems for Software 2.0
03:30 PM (Spotlights)		Thu Track 1 -- Session 2 Robust Subspace Approximation in a Stream	Thu Track 3 -- Session 2 A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization	Thu Track 2 -- Session 2 Hyperbolic Neural Networks
03:35 PM (Spotlights)		Efficient nonmyopic batch active search	Stochastic Chebyshev Gradient Descent for Spectral Optimization	Norm matters: efficient and accurate normalization schemes in deep networks
03:40 PM (Spotlights)		Interactive Structure Learning with Structural Query-by-Committee	LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning	Constructing Fast Network through Deconstruction of Convolution
03:45 PM (Spotlights)		Contour location via entropy reduction leveraging multiple information sources	Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames	A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
03:50 PM (Orals)		Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion	Optimal Algorithms for Non-Smooth Distributed Optimization in Networks	Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning
04:05 PM (Spotlights)		Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes	Direct Runge-Kutta Discretization Achieves Acceleration	Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
04:10 PM (Spotlights)		Learning convex bounds for linear quadratic control policy synthesis	Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives	Learning Loop Invariants for Program Verification
04:15 PM (Spotlights)		Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning	(Probably) Concave Graph Matching	DeepProbLog: Neural Probabilistic Logic Programming
04:20 PM (Spotlights)		Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models	Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization	Learning to Infer Graphics Programs from Hand-Drawn Images
04:25 PM (Orals)		Non-delusional Q-learning and value-iteration	Smoothed analysis of the low-rank approach for smooth semidefinite programs	Learning to Reconstruct Shapes from Unseen Classes
04:40 PM (Spotlights)		Bilevel learning of the Group Lasso structure	Wasserstein Distributionally Robust Kalman Filtering	Improving Neural Program Synthesis with Inferred Execution Traces
04:45 PM (Spotlights)		Binary Classification from Positive-Confidence Data	Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters	ResNet with one-neuron hidden layers is a Universal Approximator
04:50 PM (Spotlights)		Fully Understanding The Hashing Trick	Robust Hypothesis Testing Using Wasserstein Uncertainty Sets	Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation
04:55 PM (Spotlights)		Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds	Convergence of Cubic Regularization for Nonconvex Optimization under KL Property	Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels
05:00 PM (Posters)	Thu Poster Session B				Thu Poster Session B

Time	Room 518	Room 220 E	Room 510 ABCD	Room 517 B	Room 512 ABEF	Room 516 AB	Room 220 C	Room 517 D	Room 514	Room 513DEF	Room 220 D	Room 516 CDE	Room 517 C	Room 519	Room 515	Room 513 ABC	Room 511 ABDE	Room 517 A	Room 511 CF	Room 512 CDGH
Fri Dec 07, 2018
08:00 AM (Workshops)	NeurIPS 2018 Competition Track Day 1	Deep Reinforcement Learning	MLSys: Workshop on Systems for ML and Open Source Software	NIPS 2018 workshop on Compact Deep Neural Networks with industrial applications	Smooth Games Optimization and Machine Learning	Workshop on Ethical, Social and Governance Issues in AI	Causal Learning	All of Bayesian Nonparametrics (Especially the Useful Bits)	2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2)	Workshop on Security in Machine Learning	Bayesian Deep Learning	Imitation Learning and its Challenges in Robotics	Modeling the Physical World: Learning, Perception, and Control	The second Conversational AI workshop – today's practice and tomorrow's potential	Machine Learning for Geophysical & Geochemical Signals	Modeling and decision-making in the spatiotemporal domain	Critiquing and Correcting Trends in Machine Learning	Continual Learning	Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy	Visually grounded interaction and language

Time	Room 518	Room 220 E	Room 517 B	Room 512 ABEF	Room 516 AB	Room 517 D	Room 514	Room 513DEF	Room 220 D	Room 516 CDE	Room 517 C	Room 519	Room 515	Room 513 ABC	Room 511 ABDE	Room 517 A	Room 511 CF	Room 512 CDGH	Room 510 BD	Room 510 AC	Room 524	Rooms 220 ABC Room 210 ABCD
Sat Dec 08, 2018
08:00 AM (Workshops)	Second Workshop on Machine Learning for Creativity and Design	NIPS 2018 Workshop on Meta-Learning	AI for social good	Wordplay: Reinforcement and Language Learning in Text-based Games	Learning by Instruction	Machine Learning for Health (ML4H): Moving beyond supervised learning in healthcare	NIPS Workshop on Machine Learning for Intelligent Transportation Systems 2018	Interpretability and Robustness in Audio, Speech, and Language	Integration of Deep Learning Theories	Infer to Control: Probabilistic Reinforcement Learning and Structured Control	Reinforcement Learning under Partial Observability	Machine Learning for Molecules and Materials	Machine Learning Open Source Software 2018: Sustainable communities	Medical Imaging meets NIPS	CiML 2018 - Machine Learning competitions "in the wild": Playing in the real world or in real time	Relational Representation Learning	NeurIPS 2018 Competition Track Day 2	Privacy Preserving Machine Learning	Machine Learning for the Developing World (ML4D): Achieving sustainable impact	Machine Learning for Systems	Emergent Communication Workshop
09:30 PM (Breaks)																						Closing Reception

Mon Dec 03, 2018

Tue Dec 04, 2018

Wed Dec 05, 2018

Thu Dec 06, 2018

Fri Dec 07, 2018

Sat Dec 08, 2018