Papers
Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks
Seungjoo Yoo, Hyojin Bahng, Sunghyo Chung et al.
Color-Sensitive Person Re-Identification
Guan'an Wang, Yang Yang, Jian Cheng et al.
Columbia at SemEval-2019 Task 7: Multi-task Learning for Stance Classification and Rumour Verification
Zhuoran Liu, Shivali Goel, Mukund Yelahanka Raghuprasad et al.
ColumbiaNLP at SemEval-2019 Task 8: The Answer is Language Model Fine-tuning
Tuhin Chakrabarty, Smaranda Muresan
Co-manifold learning with missing data
Gal Mishne, Eric Chi, Ronald Coifman
Combating Adversarial Misspellings with Robust Word Recognition
Danish Pruthi, Bhuwan Dhingra, Zachary C. Lipton
Combating Label Noise in Deep Learning using Abstention
Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes et al.
Combinatorial Algorithms for Optimal Design
Vivek Madan, Mohit Singh, Uthaipon Tantipongpipat et al.
Combinatorial Attacks on Binarized Neural Networks
Elias B Khalil, Amrita Gupta, Bistra Dilkina
Combinatorial Bandits with Relative Feedback
Aadirupa Saha, Aditya Gopalan
Combinatorial Bayesian Optimization using the Graph Cartesian Product
Changyong Oh, Jakub Tomczak, Efstratios Gavves et al.
Combinatorial Inference against Label Noise
Paul Hongsuck Seo, Geeho Kim, Bohyung Han
Combinatorial Persistency Criteria for Multicut and Max-Cut
Jan-Hendrik Lange, Bjoern Andres, Paul Swoboda
Combined Reinforcement Learning via Abstract Representations
Vincent Francois-Lavet, Yoshua Bengio, Doina Precup et al.
Combining 3D Morphable Models: A Large Scale Face-And-Head Model
Stylianos Ploumpis, Haoyang Wang, Nick Pears et al.
Combining ADMM and the Augmented Lagrangian Method for Efficiently Handling Many Constraints
Joachim Giesen, Soeren Laue
Combining Adversarial Training and Disentangled Speech Representation for Robust Zero-Resource Subword Modeling
Siyuan Feng, Tan Lee, Zhiyuan Peng
Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference
Masashi Yoshikawa, Koji Mineshima, Hiroshi Noji et al.
Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise
Nikhil Krishnaswamy, Scott Friedman, James Pustejovsky
Combining Deep Learning and Verification for Precise Object Instance Detection
Siddharth Ancha, Junyu Nan, David Held
Combining Discourse Markers and Cross-lingual Embeddings for Synonym–Antonym Classification
Michael Roth, Shyam Upadhyay
Combining Distant and Direct Supervision for Neural Relation Extraction
Iz Beltagy, Kyle Lo, Waleed Ammar
Combining Fact Extraction and Verification with Neural Semantic Matching Networks
Yixin Nie, Haonan Chen, Mohit Bansal
Combining Generative and Discriminative Models for Hybrid Inference
Victor Garcia Satorras, Zeynep Akata, Max Welling
Combining Global Sparse Gradients with Local Gradients in Distributed Neural Network Training
Alham Fikri Aji, Kenneth Heafield, Nikolay Bogoychev