557 Results
August 16, 2018
Constrained Bayesian Optimization with Noisy Experiments
Bayesian Analysis 2018
We derive an expression for expected improvement under greedy batch optimization with noisy observations and noisy constraints, and develop a quasi-Monte Carlo approximation that allows it to be efficiently optimized.
By: Ben Letham, Brian Karrer, Guilherme Ottoni, Eytan Bakshy
Data Science
Machine Learning August 14, 2018
Deep Appearance Models for Face Rendering
ACM SIGGRAPH
We introduce a deep appearance model for rendering the human face. Inspired by Active Appearance Models, we develop a data-driven rendering pipeline that learns a joint representation of facial geometry and appearance from a multiview capture setup.
By: Stephen Lombardi, Jason Saragih, Tomas Simon, Yaser Sheikh
AR/VR 
Computer Vision August 13, 2018
Unsupervised Generation of Free-Form and Parameterized Avatars
TPAMI: SI: ICCV
We study two problems involving the task of mapping images between different domains. The first problem, transfers an image in one domain to an analog image in another domain. The second problem, extends the previous one by mapping an input image to a tied pair, consisting of a vector of parameters and an image that is created using a graphical engine from this vector of parameters.
By: Adam Polyak, Yaniv Taigman, Lior WolfJuly 29, 2018
Online Optical Marker-based Hand Tracking with Deep Labels
Special Interest Group on Computer Graphics and Interactive Techniques (SIGGRAPH)
We propose a technique that frames the labeling problem as a keypoint regression problem conducive to a solution using convolutional neural networks.
By: Shangchen Han, Beibei Liu, Robert Wang, Yuting Ye, Christopher D. Twigg, Kenrick Kin
Human Computer Interaction & UX July 20, 2018
Controllable Abstractive Summarization
ACL NMT Workshop
We present a neural summarization model with a simple but effective mechanism to enable users to specify these high level attributes in order to control the shape of the final summaries to better suit their needs.
By: Angela Fan, David Grangier, Michael Auli
Facebook AI Research July 18, 2018
What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties
Association for Computational Linguistics (ACL)
We introduce here 10 probing tasks designed to capture simple linguistic features of sentences, and we use them to study embeddings generated by three different encoders trained in eight distinct ways, uncovering intriguing properties of both encoders and training methods.
By: Alexis Conneau, Germán Kruszewski, Guillaume Lample, LoÏc Barrault, Marco Baroni
Natural Language Processing & Speech July 16, 2018
Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora
Association for Computational Linguistics (ACL)
Methods for unsupervised hypernym detection may broadly be categorized according to two paradigms: pattern-based and distributional methods. In this paper, we study the performance of both approaches on several hypernymy tasks and find that simple pattern-based methods consistently outperform distributional methods on common benchmark datasets.
By: Stephen Roller, Douwe Kiela, Maximilian NickelJuly 15, 2018
Personalizing Dialogue Agents: I have a dog, do you have pets too?
Association for Computational Linguistics (ACL)
Chit-chat models are known to have several problems: they lack specificity, do not display a consistent personality and are often not very captivating. In this work we present the task of making chit-chat more engaging by conditioning on profile information.
By: Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, Jason WestonJuly 15, 2018
Hierarchical Neural Story Generation
Association for Computational Linguistics (ACL)
We explore story generation: creative systems that can build coherent and fluent passages of text about a topic. We collect a large dataset of 300K human-written stories paired with writing prompts from an online forum.
By: Angela Fan, Michael Lewis, Yann DauphinJuly 15, 2018
Filtering and Mining Parallel Data in a Joint Multilingual Space
Association for Computational Linguistics (ACL)
We learn a joint multilingual sentence embedding and use the distance between sentences in different languages to filter noisy parallel data and to mine for parallel data in large news collections.
By: Holger Schwenk