【NIPS2018】接收论文列表

【导读】NIPS2018论文一览



Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning

Ofir Marom · Benjamin Rosman


Poster


The Price of Fair PCA: One Extra dimension

Samira Samadi · Uthaipon Tantipongpipat · Jamie Morgenstern · Mohit Singh · Santosh Vempala


Poster


Transfer of Deep Reactive Policies for MDP Planning

Aniket Bajpai · Sankalp Garg · Mausam


Poster


Sequential Data Classification for Resource-constrained Devices

Prateek Jain · Harsha Vardhan Simhadri · Don Dennis ·


Poster


Sparse PCA from Sparse Linear Regression

Madalina Persu · Guy Bresler · Sam Park


Poster


Computationally and Statistically Efficient Learning of Bayes Nets Using Path Queries

Kevin Bello · Jean Honorio


Poster


Point process latent variable models of freely swimming larval zebrafish

Anuj Sharma · Scott Linderman · Robert Johnson · Florian Engert


Poster


Contrastive Learning from Pairwise Measurements

· Zhuoran Yang · Yuchen Xie · Princeton Zhaoran Wang

Poster


Topkapi: Parallel and Fast Algorithm for Finding Top-K Frequent Elements

Ankush Mandal · He Jiang · Anshumali Shrivastava · Vivek Sarkar


Poster


Removing Hidden Confounding by Experimental Grounding

Uri Shalit · Nathan Kallus · Aahlad Manas Puli


Poster


Semidefinite relaxations for certifying robustness to adversarial examples

Aditi Raghunathan · Percy Liang · Jacob Steinhardt


Poster


MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization

Ian En-Hsu Yen · Pradeep Ravikumar · Shou-De Lin · Wei-Cheng Lee


Poster


Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons

Nima Anari · Constantinos Daskalakis · Wolfgang Maass · Christos Papadimitriou · Amin Saberi · Santosh Vempala


Poster


Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions

Sara Magliacane · Thijs van Ommen · Tom Claassen · Stephan Bongers · Philip Versteeg · Joris M Mooij


Poster


Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations

Tong Wang


Poster


Differentially Private Change-Point Detection

Sara Krehbiel · Rachel Cummings · Wanrong Zhang · Yajun Mei · Rui Tuo


Poster


Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds

Raghav Somani · Chirag Gupta · Prateek Jain · Praneeth Netrapalli


Poster


Fast and Effective Robustness Certification

Gagandeep Singh · Timon Gehr · Matthew Mirman · Markus Püschel · Martin Vechev

Poster


Bias and Generalization in Deep Generative Models: An Empirical Study

Shengjia Zhao · Hongyu Ren · Arianna Yuan · Jiaming Song · Stefano Ermon


Poster


Learning Temporal Point Processes via Reinforcement Learning

Shuang Li · SHUAI XIAO · Shixiang Zhu · Nan Du · Yao Xie · Le Song


Poster


Benefits of overparameterization with EM

Ji Xu · Daniel Hsu · Arian Maleki


Poster


Learning Beam Search Policies via Imitation Learning

Renato Negrinho · Matthew Gormley · Geoffrey Gordon


Poster


Data-Driven Clustering

Maria-Florina Balcan · Travis Dick · Colin White


Poster


Understanding Regularized Spectral Clustering via Graph Conductance

Yilin Zhang · Karl Rohe


Poster


Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices

Jinhwan Park · Yoonho Boo · Iksoo Choi · Sungho Shin · Wonyong Sung


Poster


Connecting Optimization and Regularization Paths

Arun Suggala · Adarsh Prasad · Pradeep Ravikumar


Poster


Sketching Method for Large Scale Combinatorial Inference

Wei Sun · Junwei Lu · Han Liu


Poster


Regret Bounds for Online Portfolio Selection with a Cardinality Constraint

Shinji Ito · Daisuke Hatano · Sumita Hanna · Akihiro Yabe · Takuro Fukunaga · Naonori Kakimura · Ken-Ichi Kawarabayashi


Poster


Improved Network Robustness with Adversary Critic

Alexander Matyasko · Lap-Pui Chau

Poster


Fast deep reinforcement learning using online adjustments from the past

Steven Hansen · Alexander Pritzel · Pablo Sprechmann · Andre Barreto · Charles Blundell


Poster


Streamlining constraints for random k-SAT

Aditya Grover · Tudor Achim


Poster


Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders

Abubakar Abid · James Zou


Poster


Gated Complex Recurrent Neural Networks

Moritz Wolter ·


Poster


Bayesian Structure Learning by Recursive Bootstrap

Raanan Yehezkel Rohekar · Yaniv Gurwicz · shami nisimov · Guy Koren · Gal Novik


Poster


The Sparse Manifold Transform

Yubei Chen · Dylan Paiton · Bruno A Olshausen


Poster


Deep Generative Models with Learnable Knowledge Constraints

Zhiting Hu · Zichao Yang · Ruslan Salakhutdinov · LIANHUI Qin · Xiaodan Liang · Haoye Dong · Eric Xing


Poster


Diversity-Driven Exploration Strategy for Deep Reinforcement Learning

Zhang-Wei Hong · Tzu-Yun Shann · Shih-Yang Su · Yi-Hsiang Chang · Tsu-Jui Fu · Chun-Yi Lee


Poster


Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior

Zi Wang · Beomjoon Kim · Leslie Kaelbling


Poster


Discretely Relaxing Continuous Variables for tractable Variational Inference

Trefor Evans · Prasanth Nair


Poster


Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise

Mantas Mazeika · Dan Hendrycks


Poster


Temporal alignment and latent Gaussian process factor inference in population spike trains

Lea Duncker · Maneesh Sahani


Poster


Bounded-Loss Private Prediction Markets

Rafael Frongillo · Bo Waggoner


Poster


Learning Abstract Options

Matthew Riemer · Miao Liu · Gerald Tesauro


Poster


Deep Learning for Supercomputers: Distributed Tensor Layouts Define Distributed Computation

Noam Shazeer · Niki Parmar · Youlong Cheng · Ashish Vaswani · Mingsheng Hong · Peter Hawkins · Cliff Young · HyoukJoong Lee

Poster


Convex Elicitation of Continuous Properties

Jessica Finocchiaro · Rafael Frongillo


Poster


Context-aware Synthesis and Placement of Object Instances

Donghoon Lee · Ming-Yu Liu · Ming-Hsuan Yang · Sifei Liu · Jinwei Gu · Jan Kautz


Poster


3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data

Maurice Weiler · Wouter Boomsma · Mario Geiger · Max Welling · Taco Cohen


Poster


Gaussian Process Prior Variational Autoencoders

Francesco Paolo Casale · Luca Saglietti · Jennifer Listgarten · Nicolo Fusi · Adrian Dalca


Poster


Adversarial Risk and Robustness for Discrete Distributions

Dimitrios Diochnos · Saeed Mahlouji Far · Mohammad Mahmoody


Poster


Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound

Hadi Kazemi · Sobhan Soleymani · Fariborz Taherkhani · Ali Dabouei · Seyed Iranmanesh ·


Poster


Using Quantum Graphical Models to Perform Inference in Hilbert Space

Siddarth Srinivasan · Carlton Downey · Byron Boots


Poster


Lifted Weighted Mini-Bucket

Nicholas Gallo · Alexander Ihler


Poster


Learning to solve SMT formulas

Mislav Balunovic · Pavol Bielik · Martin Vechev


Poster


PCA of high dimensional stochastic processes

Joseph Antognini · Jascha Sohl-Dickstein


Poster


Improving Simple Models with Confidence Profiles

Amit Dhurandhar · Karthikeyan Shanmugam · Ronny Luss · Peder A Olsen


Poster


Robust Learning of Fixed-Structure Bayesian Networks

Yu Cheng · Ilias Diakonikolas · Daniel Kane · Alistair Stewart


Poster


Learning conditional GAN using noisy labels

Kiran Thekumparampil · Ashish Khetan · Sewoong Oh

Poster


Predictive Approximate Bayesian Computation via Saddle Points

Yingxiang Yang · Bo Dai · Niao He · Negar Kiyavash


Poster


Learning to Share and Hide Intentions using Information Regularization

DJ Strouse · Max Kleiman-Weiner · Josh Tenenbaum · Matt Botvinick · David Schwab


Poster


Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions

Boris Muzellec · marco Cuturi


Poster


Glow: Generative Flow with Invertible 1x1 Convolutions

Durk Kingma · Prafulla Dhariwal


Poster


Total stochastic gradient algorithms and applications in reinforcement learning

Paavo Parmas


Poster


Learning with SGD and Random Features

Luigi Carratino · Lorenzo Rosasco · Alessandro Rudi


Poster


Backpropagation with Callbacks: Towards Efficient and Expressive Differentiable Programming

Fei Wang · James Decker · Xilun Wu · Gregory Essertel · Tiark Rompf


Poster


Learning To Learn Around A Common Mean

Massimiliano Pontil · giulia.denevi@gmail.com Denevi · Carlo Ciliberto · Dimitris Stamos


Poster


Human-in-the-Loop Interpretability Prior

Isaac Lage · Andrew Ross · Samuel J Gershman · Been Kim · Finale Doshi-Velez


Poster


Synaptic Strength For Convolutional Neural Network

CHEN LIN · Zhao Zhong · Wu Wei


Poster


A Spectral View of Adversarially Robust Features

Shivam Garg · Vatsal Sharan · Gregory Valiant · Brian Zhang


Poster


Bayesian Nonparametric Spectral Estimation

Felipe Tobar


Poster


Clebsch–Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network

Risi Kondor · Zhen Lin · Shubhendu Trivedi


Poster


A Simple Cache Model for Image Recognition

Emin Orhan


Poster


Low-rank Tucker decomposition of large tensors using TensorSketch

Osman Asif Malik · Stephen Becker


Poster


Blockwise Parallel Decoding for Deep Autoregressive Models

Mitchell Stern · Noam Shazeer · Jakob Uszkoreit


Poster


Thwarting Adversarial Examples: An  L 0 -Robust Sparse Fourier Transform

Nikhil Vyas · Jack Murtagh · Mitali Bafna

Poster


Testing for Families of Distributions via the Fourier Transform

Alistair Stewart · Ilias Diakonikolas · Clement Canonne


Poster


A Retrieve-and-Edit Framework for Predicting Structured Outputs

Tatsunori B Hashimoto · Kelvin Guu · Yonatan Oren · Percy Liang


Poster


Scalable Laplacian K-modes

Imtiaz Ziko · Ismail Ben Ayed · Eric Granger


Poster


Blind Deconvolutional Phase Retrieval via Convex Programming

Ali Ahmed · Alireza Aghasi · Paul Hand


Poster


Neural Voice Cloning with a Few Samples

Sercan Arik · Jitong Chen · Kainan Peng · Wei Ping · Yanqi Zhou


Poster


Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams

Tam Le · Makoto Yamada


Poster


Memory Augmented Policy Optimization for Program Synthesis with Generalization

Chen Liang · Mohammad Norouzi · Jonathan Berant · Quoc V Le · Ni Lao


Poster


Learning to Reason with Third Order Tensor Products

Imanol Schlag · Jürgen Schmidhuber


Poster


Post: Device Placement with Cross-Entropy Minimization and Proximal Policy Optimization

Yuanxiang Gao · Li Chen · Baochun Li


Poster


Using Large Ensembles of Control Variates for Variational Inference

Tomas Geffner · Justin Domke


Poster


Non-delusional Q-learning and Value-iteration

Tyler Lu · Craig Boutilier · Dale Schuurmans


Poster


Learning Invariances using the Marginal Likelihood

Mark van der Wilk · Matthias Bauer · ST John · James Hensman


Poster


Uplift Modeling from Separate Labels

Ikko Yamane · Florian Yger · Jamal Atif · Masashi Sugiyama


Poster


Online Robust Policy Learning in the Presence of Unknown Adversaries

Aaron Havens · Zhanhong Jiang · Soumik Sarkar

Poster


Variance-Reduced Stochastic Gradient Descent on Streaming Data

Ellango Jothimurugesan · Ashraf Tahmasbi · Phillip Gibbons · Srikanta Tirthapura


Poster


On Markov Chain Gradient Descent

Tao Sun · Yuejiao Sun · Wotao Yin


Poster


Maximizing acquisition functions for Bayesian optimization

James Wilson · Frank Hutter · Marc Deisenroth


Poster


Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies

Alessandro Achille · Tom Eccles · Loic Matthey · Chris Burgess · Nicholas Watters · Alexander Lerchner · Irina Higgins


Poster


Dynamic Network Model from Partial Observations

Elahe Ghalebi · Baharan Mirzasoleiman · Radu Grosu · Jure Leskovec


Poster


ATOMO: Communication-efficient Learning via Atomic Sparsification

Zachary B Charles · Hongyi Wang · Scott Sievert · Dimitris Papailiopoulos · Stephen Wright


Poster


Reinforcement Learning for Solving the Vehicle Routing Problem

· Afshin Oroojlooy · Lawrence Snyder · Martin Takac


Poster


Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation

Matthew O'Kelly · Aman Sinha · Hongseok Namkoong · Russ Tedrake · John C Duchi


Poster


Temporal abstraction for recurrent dynamical models

Alexander Neitz · Giambattista Parascandolo · Stefan Bauer · Bernhard Schölkopf


Poster


Object-Oriented Dynamics Predictor

Guangxiang Zhu · Chongjie Zhang


Poster


Adaptive Methods for Nonconvex Optimization

Manzil Zaheer · Sashank Reddi · Devendra Sachan · Satyen Kale · Sanjiv Kumar


Poster


Entropy Rate Estimation for Markov Chains with Large State Space

Yanjun Han · Jiantao Jiao · Chuan-Zheng Lee · Tsachy Weissman · Yihong Wu · Tiancheng Yu


Poster


Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport

Theo Lacombe · marco Cuturi · Steve OUDOT


Poster


Deep Anomaly Detection Using Geometric Transformations

Izhak Golan · Ran El-Yaniv


Poster


Generalization Bounds for Uniformly Stable Algorithms

Vitaly Feldman · Jan Vondrak


Poster


Unsupervised Depth Estimation, 3D Face Rotation and Replacement

Joel Moniz · Christopher Beckham · Sina Honari · Chris Pal


Poster


Towards Deep Conversational Recommendations

Raymond Li · Samira Ebrahimi Kahou · Hannes Schulz · Vincent Michalski · Laurent Charlin · Chris Pal


Poster


Latent Alignment and Variational Attention

Yoon Kim · Yuntian Deng · Justin Chiu · Demi Guo · Alexander Rush

Poster


Improving Explorability in Variational Inference with Annealed Variational Objectives

Chin-Wei Huang · Shawn Tan · Alexandre Lacoste · Aaron C Courville


Poster


Coupled Variational Bayes via Optimization Embedding

Bo Dai · Hanjun Dai · Niao He · Weiyang Liu · Zhen Liu · Jianshu Chen · Lin Xiao · Le Song


Poster


Theoretical guarantees for EM under misspecified Gaussian mixture models

Raaz Dwivedi · nhật Hồ · Koulik Khamaru · Martin Wainwright · Michael Jordan


Poster


Non-convex Optimization with Discretized Diffusions

Murat A Erdogdu · Lester Mackey · Ohad Shamir


Poster


Improving Online Algorithms via ML Predictions

Manish Purohit · Zoya Svitkina · Ravi Kumar


Poster


Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization

Hoi-To Wai · Princeton Zhaoran Wang · Zhuoran Yang · Mingyi Hong


Poster


Ex ante correlation and collusion in zero-sum multi-player extensive-form games

Andrea Celli · Gabriele Farina · Nicola Gatti · Tuomas Sandholm


Poster


Invertibility of Convolutional Generative Networks from Partial Measurements

Fangchang Ma · Ulas Ayaz · Sertac Karaman


Poster


Trading robust representations for sample complexity through self-supervised visual experience

Andrea Tacchetti · Stephen Voinea · Georgios Evangelopoulos


Poster


An intriguing failing of convolutional neural networks and the CoordConv solution

Rosanne Liu · Joel Lehman · Eric Frank · Felipe Petroski Such · Alex Sergeev · Jason Yosinski


Poster


Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization

Rad Niazadeh · Tim Roughgarden · Joshua Wang


Poster


To What Extent Do Different Neural Networks Learn the Same Representation: A Neuron Activation Subspace Match Approach

Liwei Wang · Lunjia Hu · Jiayuan Gu · Zhiqiang Hu · Yue Wu · Kun He · John Hopcroft


Poster


Neural Proximal Gradient Descent for Compressive Imaging

Morteza Mardani · · David Donoho · Vardan Papyan · Hatef Monajemi · Shreyas Vasanawala · John Pauly


Poster


Learning convex bounds for linear quadratic control policy synthesis

Jack Umenberger · Thomas B Schön


Poster


Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis

Thomas George · César Laurent · Xavier Bouthillier · Nicolas Ballas · Pascal Vincent


Poster


e-SNLI: Natural Language Inference with Natural Language Explanations

Oana-Maria Camburu · Tim Rocktäschel · Thomas Lukasiewicz · Phil Blunsom


Poster


Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach

Mike Gimelfarb · Scott Sanner · Chi-Guhn Lee


Poster


Uncertainty-Aware Few-Shot Learning with Probabilistic Model-Agnostic Meta-Learning

Kelvin Xu · Chelsea Finn · Sergey Levine


Poster


Sanity Checks for Saliency Maps

Julius Adebayo · Been Kim · Ian Goodfellow · Justin Gilmer · Moritz Hardt


Poster


Multi-objective Maximization of Monotone Submodular Functions with Cardinality Constraint

Rajan Udwani


Poster


PAC-Bayes Tree: weighted subtrees with guarantees

Tin Nguyen · Samory Kpotufe


Poster


DAGs with NO TEARS: Continuous Optimization for Structure Learning

Xun Zheng · Bryon Aragam · Pradeep Ravikumar · Eric Xing


Poster


Implicit Bias of Gradient Descent on Linear Convolutional Networks

Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro


Poster


Learning and Testing Causal Models with Interventions

Jayadev Acharya · Arnab Bhattacharyya · Constantinos Daskalakis · Saravanan Kandasamy


Poster


Discovering Feedback Codes via Deep Learning

Hyeji Kim · Yihan Jiang · Sreeram Kannan · Sewoong Oh · Pramod Viswanath


Poster


Identification and Estimation of Causal Effects from Dependent Data

Eli Sherman · Ilya Shpitser


Poster


Quantifying Linguistic Shifts: The Global Anchor Method and Its Applications

Zi Yin · Vinayak Sachidananda · Balaji Prabhakar


Poster


Gather-Scatter: Context Propagation for ConvNets

Jie Hu · Li Shen · Gang Sun · Samuel Albanie · Andrea Vedaldi


Poster


The emergence of multiple retinal cell types through efficient coding of natural movies

Stephane Deny · Jack Lindsey · Surya Ganguli · Samuel Ocko


Poster


Learning Attractor Dynamics for Generative Memory

Yan Wu · Tim Lillicrap · Gregory Wayne · Karol Gregor


Poster


Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures

Sergey Bartunov · Adam Santoro · Blake Richards · Geoffrey E Hinton · Tim Lillicrap


Poster


Statistical and Computational Trade-Offs in Kernel K-Means

Daniele Calandriello · Lorenzo Rosasco


Poster


Co-regularized Alignment for Unsupervised Domain Adaptation

Abhishek Kumar · Prasanna Sattigeri · kahini wadhawan · Leonid Karlinsky · Rogerio S Feris · Bill Freeman · Gregory Wornell


Poster


Hardware Conditioned Policies for Multi-Robot Transfer Learning

Tao Chen · Adithyavairavan Murali · Abhinav Gupta


Poster


Sample Complexity of Nonparametric Semi-Supervised Learning

Chen Dan · · Bryon Aragam · Pradeep Ravikumar · Eric Xing


Poster


SNIPER: Efficient Multi-Scale Training

Bharat Singh · Mahyar Najibi · Larry S Davis


Poster


The Effect of Network Width on the Performance of Large-batch Training

Lingjiao Chen · Hongyi Wang · Paraschos Koutris · Dimitris Papailiopoulos · Jinman Zhao


Poster


Representer Point Selection for Explaining Deep Neural Networks

Chih-Kuan Yeh · Joon Sik Kim · Ian En-Hsu Yen · Pradeep Ravikumar


Poster


The Importance of Sampling inMeta-Reinforcement Learning

Bradly Stadie · Ge Yang · Pieter Abbeel · Yuhuai Wu · Yan Duan · Xi Chen · Rein Houthooft · Ilya Sutskever


Poster


Confounding-Robust Policy Improvement

Angela Zhou · Nathan Kallus


Poster


Deep Dynamical Modeling and Control of Unsteady Fluid Flows

Jeremy Morton · Antony Jameson · Mykel J Kochenderfer · Freddie Witherden


Poster


Coordinate Descent with Bandit Sampling

Farnood Salehi · Patrick Thiran · Elisa Celis


Poster


The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization

Constantinos Daskalakis · Ioannis Panageas


Poster


Beyond Grids: Learning Graph Representations for Visual Recognition

Yin Li · Abhinav Gupta


Poster


PAC-Bayes bounds for stable algorithms with instance-dependent priors

Omar Rivasplata · Csaba Szepesvari · John S Shawe-Taylor · Emilio Parrado-Hernandez · Shiliang Sun

Poster


更多文章,请移步: 

https://nips.cc/Conferences/2018/Schedule?nsukey=8JsvAskSCbOUv0wSecIT2IgFjexFhUcXnAZBSk0TCEJ%2FIaAEyM88ar%2FXzvo696hHHMErnN%2ByPRZQm1HHvV6Bku6nlKw%2B4yVcD%2F%2FzYYBWyvwk8UtBxmN88evjgsqMJbSfO02CXpFec7CwGdUsFjmCp434iMmL1nI15gRQr8NzwLNFVHtKl1OVa73cPWgwhozLJPPjl8%2B%2BoxsQO8zGCZkQCg%3D%3D


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