Papers
Machine Learning with Crowdsourcing: A Brief Summary of the Past Research and Future Directions
Victor S. Sheng, Jing Zhang
Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications
Daniel S. Brown, Scott Niekum
MAi: An Intelligent Model Acquisition Interface for Interactive Specification of Dialogue Agents
Tathagata Chakraborti, Christian Muise, Shubham Agarwal et al.
Making Money from What You Know - How to Sell Information?
Shani Alkoby, Zihe Wang, David Sarne et al.
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning
Manan Tomar, Akhil Sathuluri, Balaraman Ravindran
Manifold Distance-Based Over-Sampling Technique for Class Imbalance Learning
Lingkai Yang, Yinan Guo, Jian Cheng
Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets
Zhiwu Huang, Jiqing Wu, Luc Van Gool
Marginal Inference in Continuous Markov Random Fields Using Mixtures
Yuanzhen Guo, Hao Xiong, Nicholas Ruozzi
Matrix Completion for Graph-Based Deep Semi-Supervised Learning
Fariborz Taherkhani, Hadi Kazemi, Nasser M. Nasrabadi
Matroid Constrained Fair Allocation Problem
Arpita Biswas, Siddharth Barman
MEAL: Multi-Model Ensemble via Adversarial Learning
Zhiqiang Shen, Zhankui He, Xiangyang Xue
Meaningful Explanations of Black Box AI Decision Systems
Dino Pedreschi, Fosca Giannotti, Riccardo Guidotti et al.
Measurement Maximizing Adaptive Sampling with Risk Bounding Functions
Benjamin Ayton, Brian Williams, Richard Camilli
Mechanism Design for Multi-Type Housing Markets with Acceptable Bundles
Sujoy Sikdar, Sibel Adalı, Lirong Xia
Meimei: An Efficient Probabilistic Approach for Semantically Annotating Tables
Kunihiro Takeoka, Masafumi Oyamada, Shinji Nakadai et al.
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization
Bryan Wilder, Bistra Dilkina, Milind Tambe
Memory-Augmented Temporal Dynamic Learning for Action Recognition
Yuan Yuan, Dong Wang, Qi Wang
Memory Bounded Open-Loop Planning in Large POMDPs Using Thompson Sampling
Thomy Phan, Lenz Belzner, Marie Kiermeier et al.
MeshNet: Mesh Neural Network for 3D Shape Representation
Yutong Feng, Yifan Feng, Haoxuan You et al.
Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning
Woojun Kim, Myungsik Cho, Youngchul Sung
Meta-Descent for Online, Continual Prediction
Andrew Jacobsen, Matthew Schlegel, Cameron Linke et al.
Meta Learning for Image Captioning
Nannan Li, Zhenzhong Chen, Shan Liu
Meta-Path Augmented Response Generation
Yanran Li, Wenjie Li
MetaStyle: Three-Way Trade-off among Speed, Flexibility, and Quality in Neural Style Transfer
Chi Zhang, Yixin Zhu, Song-Chun Zhu
MFBO-SSM: Multi-Fidelity Bayesian Optimization for Fast Inference in State-Space Models
Mahdi Imani, Seyede Fatemeh Ghoreishi, Douglas Allaire et al.