【NIPS2018】接收论文列表- 专知

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【NIPS2018】接收论文列表

专知出品

【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