Papers
PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors
Haowen Deng, Tolga Birdal, Slobodan Ilic
PPFNet: Global Context Aware Local Features for Robust 3D Point Matching
Haowen Deng, Tolga Birdal, Slobodan Ilic
Practical Application of Domain Dependent Confidence Measurement for Spoken Language Understanding Systems
Mahnoosh Mehrabani, David Thomson, Benjamin Stern
Practical Bayesian optimization in the presence of outliers
Ruben Martinez-Cantin, Kevin Tee, Michael McCourt
Practical Black-box Attacks on Deep Neural Networks using Efficient Query Mechanisms
Arjun Nitin Bhagoji, Warren He, Bo Li et al.
Practical Block-Wise Neural Network Architecture Generation
Zhao Zhong, Junjie Yan, Wei Wu et al.
Practical Contextual Bandits with Regression Oracles
Dylan Foster, Alekh Agarwal, Miroslav Dudik et al.
Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching
Stepan Tulyakov, Anton Ivanov, François Fleuret
Practical exact algorithm for trembling-hand equilibrium refinements in games
Gabriele Farina, Nicola Gatti, Tuomas Sandholm
Practical Methods for Graph Two-Sample Testing
Debarghya Ghoshdastidar, Ulrike von Luxburg
Practical Parsing for Downstream Applications
Daniel Dakota, Sandra Kübler
Pragmatically Informative Image Captioning with Character-Level Inference
Reuben Cohn-Gordon, Noah Goodman, Christopher Potts
prDeep: Robust Phase Retrieval with a Flexible Deep Network
Christopher Metzler, Phillip Schniter, Ashok Veeraraghavan et al.
Pre- and In-Parsing Models for Neural Empty Category Detection
Yufei Chen, Yuanyuan Zhao, Weiwei Sun et al.
Precision and Recall for Time Series
Nesime Tatbul, Tae Jun Lee, Stan Zdonik et al.
PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution
Hong Chen, Zhenhua Fan, Hao Lu et al.
Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification
Chih-Yang Hsia, Wei-Lin Chiang, Chih-Jen Lin
PredCNN: Predictive Learning with Cascade Convolutions
Ziru Xu, Yunbo Wang, Mingsheng Long et al.
Predefined Sparseness in Recurrent Sequence Models
Thomas Demeester, Johannes Deleu, Fréderic Godin et al.
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction
Nataly Brukhim, Amir Globerson
Predicting accuracy on large datasets from smaller pilot data
Mark Johnson, Peter Anderson, Mark Dras et al.
Predicting Activity and Location with Multi-task Context Aware Recurrent Neural Network
Dongliang Liao, Weiqing Liu, Yuan Zhong et al.
Predicting Adolescents’ Educational Track from Chat Messages on Dutch Social Media
Lisa Hilte, Walter Daelemans, Reinhild Vandekerckhove
Predicting and interpreting embeddings for out of vocabulary words in downstream tasks
Nicolas Garneau, Jean-Samuel Leboeuf, Luc Lamontagne