MLJ 2020

79 papers

A Bad Arm Existence Checking Problem: How to Utilize Asymmetric Problem Structure? Koji Tabata, Atsuyoshi Nakamura, Junya Honda, Tamiki Komatsuzaki

A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework Homayun Afrabandpey, Tomi Peltola, Juho Piironen, Aki Vehtari, Samuel Kaski

A Survey on Semi-Supervised Learning Jesper E. van Engelen, Holger H. Hoos

Active Deep Q-Learning with Demonstration Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama

Ada-Boundary: Accelerating DNN Training via Adaptive Boundary Batch Selection Hwanjun Song, Sundong Kim, Minseok Kim, Jae-Gil Lee

An Empirical Analysis of Binary Transformation Strategies and Base Algorithms for Multi-Label Learning Adriano Rivolli, Jesse Read, Carlos Soares, Bernhard Pfahringer, André C. P. L. F. de Carvalho

An Evaluation of Machine-Learning for Predicting Phenotype: Studies in Yeast, Rice, and Wheat Nastasiya F. Grinberg, Oghenejokpeme I. Orhobor, Ross D. King

Analysis of Hannan Consistent Selection for Monte Carlo Tree Search in Simultaneous Move Games Vojtech Kovarík, Viliam Lisý

Anomaly Detection with Inexact Labels Tomoharu Iwata, Machiko Toyoda, Shotaro Tora, Naonori Ueda

Binary Classification with Ambiguous Training Data Naoya Otani, Yosuke Otsubo, Tetsuya Koike, Masashi Sugiyama

Bonsai: Diverse and Shallow Trees for Extreme Multi-Label Classification Sujay Khandagale, Han Xiao, Rohit Babbar

Boost Image Captioning with Knowledge Reasoning Feicheng Huang, Zhixin Li, Haiyang Wei, Canlong Zhang, Huifang Ma

Classification Using Proximity Catch Digraphs Artür Manukyan, Elvan Ceyhan

Classification with Costly Features as a Sequential Decision-Making Problem Jaromír Janisch, Tomás Pevný, Viliam Lisý

Co-Eye: A Multi-Resolution Ensemble Classifier for Symbolically Approximated Time Series Zahraa S. Abdallah, Mohamed Medhat Gaber

Combining Bayesian Optimization and Lipschitz Optimization Mohamed Osama Ahmed, Sharan Vaswani, Mark Schmidt

Communication-Efficient Distributed Multi-Task Learning with Matrix Sparsity Regularization Qiang Zhou, Yu Chen, Sinno Jialin Pan

Conditional Density Estimation and Simulation Through Optimal Transport Esteban G. Tabak, Giulio Trigila, Wenjun Zhao

Constructing Generative Logical Models for Optimisation Problems Using Domain Knowledge Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff

Correction to: Efficient Feature Selection Using Shrinkage Estimators Konstantinos Sechidis, Laura Azzimonti, Adam Craig Pocock, Giorgio Corani, James Weatherall, Gavin Brown

Correction to: Robust Classification via MOM Minimization Guillaume Lecué, Matthieu Lerasle, Timothée Mathieu

Detecting Anomalous Packets in Network Transfers: Investigations Using PCA, Autoencoder and Isolation Forest in TCP Mariam Kiran, Cong Wang, George Papadimitriou, Anirban Mandal, Ewa Deelman

Discovering Subjectively Interesting Multigraph Patterns Sarang Kapoor, Dhish Kumar Saxena, Matthijs van Leeuwen

Distributed Block-Diagonal Approximation Methods for Regularized Empirical Risk Minimization Ching-Pei Lee, Kai-Wei Chang

Double Random Forest Sunwoo Han, Hyunjoong Kim, Yung-Seop Lee

Effective Approximation of Parametrized Closure Systems over Transactional Data Streams Daniel Trabold, Tamás Horváth, Stefan Wrobel

Embedding-Based Silhouette Community Detection Blaz Skrlj, Jan Kralj, Nada Lavrac

Engineering Problems in Machine Learning Systems Hiroshi Kuwajima, Hirotoshi Yasuoka, Toshihiro Nakae

Ensembles of Extremely Randomized Predictive Clustering Trees for Predicting Structured Outputs Dragi Kocev, Michelangelo Ceci, Tomaz Stepisnik

Evaluating Time Series Forecasting Models: An Empirical Study on Performance Estimation Methods Vítor Cerqueira, Luís Torgo, Igor Mozetic

Exploiting Causality in Gene Network Reconstruction Based on Graph Embedding Gianvito Pio, Michelangelo Ceci, Francesca Prisciandaro, Donato Malerba

Fast and Accurate Pseudoinverse with Sparse Matrix Reordering and Incremental Approach Jinhong Jung, Lee Sael

Fast Greedy C-Bound Minimization with Guarantees Baptiste Bauvin, Cécile Capponi, Jean-Francis Roy, François Laviolette

Feature Ranking for Multi-Target Regression Matej Petkovic, Dragi Kocev, Saso Dzeroski

Few-Shot Learning with Adaptively Initialized Task Optimizer: A Practical Meta-Learning Approach Han-Jia Ye, Xiang-Rong Sheng, De-Chuan Zhan

Gradient Descent Optimizes Over-Parameterized Deep ReLU Networks Difan Zou, Yuan Cao, Dongruo Zhou, Quanquan Gu

Handling Concept Drift via Model Reuse Peng Zhao, Le-Wen Cai, Zhi-Hua Zhou

High-Dimensional Bayesian Optimization Using Low-Dimensional Feature Spaces Riccardo Moriconi, Marc Peter Deisenroth, K. S. Sesh Kumar

High-Dimensional Model Recovery from Random Sketched Data by Exploring Intrinsic Sparsity Tianbao Yang, Lijun Zhang, Qihang Lin, Shenghuo Zhu, Rong Jin

Imbalanced Regression and Extreme Value Prediction Rita P. Ribeiro, Nuno Moniz

Improved Graph-Based SFA: Information Preservation Complements the Slowness Principle Alberto N. Escalante-B., Laurenz Wiskott

Improving Coordination in Small-Scale Multi-Agent Deep Reinforcement Learning Through Memory-Driven Communication Emanuele Pesce, Giovanni Montana

Incremental Predictive Clustering Trees for Online Semi-Supervised Multi-Target Regression Aljaz Osojnik, Pance Panov, Saso Dzeroski

Inductive General Game Playing Andrew Cropper, Richard Evans, Mark Law

Joint Consensus and Diversity for Multi-View Semi-Supervised Classification Wenzhang Zhuge, Chenping Hou, Shaoliang Peng, Dongyun Yi

Joint Maximization of Accuracy and Information for Learning the Structure of a Bayesian Network Classifier Dan Halbersberg, Maydan Wienreb, Boaz Lerner

Kappa Updated Ensemble for Drifting Data Stream Mining Alberto Cano, Bartosz Krawczyk

Learning from Positive and Unlabeled Data: A Survey Jessa Bekker, Jesse Davis

Learning Higher-Order Logic Programs Andrew Cropper, Rolf Morel, Stephen H. Muggleton

Learning Representations from Dendrograms Morteza Haghir Chehreghani, Mostafa Haghir Chehreghani

Learning with Mitigating Random Consistency from the Accuracy Measure Jieting Wang, Yuhua Qian, Feijiang Li

Logical Reduction of Metarules Andrew Cropper, Sophie Tourret

Model-Based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models Yu Nishiyama, Motonobu Kanagawa, Arthur Gretton, Kenji Fukumizu

Multi-Label Feature Ranking with Ensemble Methods Matej Petkovic, Saso Dzeroski, Dragi Kocev

Multi-Label Optimal Margin Distribution Machine Zhi-Hao Tan, Peng Tan, Yuan Jiang, Zhi-Hua Zhou

On Cognitive Preferences and the Plausibility of Rule-Based Models Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim

On Some Graph-Based Two-Sample Tests for High Dimension, Low Sample Size Data Soham Sarkar, Rahul Biswas, Anil Kumar Ghosh

Online Bayesian Max-Margin Subspace Learning for Multi-View Classification and Regression Jia He, Changying Du, Fuzhen Zhuang, Xin Yin, Qing He, Guoping Long

Predicting Rice Phenotypes with Meta and Multi-Target Learning Oghenejokpeme I. Orhobor, Nickolai N. Alexandrov, Ross D. King

Predictive Spreadsheet Autocompletion with Constraints Samuel Kolb, Stefano Teso, Anton Dries, Luc De Raedt

Principled Analytic Classifier for Positive-Unlabeled Learning via Weighted Integral Probability Metric Yongchan Kwon, Wonyoung Kim, Masashi Sugiyama, Myunghee Cho Paik

Propositionalization and Embeddings: Two Sides of the Same Coin Nada Lavrac, Blaz Skrlj, Marko Robnik-Sikonja

Provable Accelerated Gradient Method for Nonconvex Low Rank Optimization Huan Li, Zhouchen Lin

Rank Minimization on Tensor Ring: An Efficient Approach for Tensor Decomposition and Completion Longhao Yuan, Chao Li, Jianting Cao, Qibin Zhao

Rankboost+: An Improvement to Rankboost Harold S. Connamacher, Nikil Pancha, Rui Liu, Soumya Ray

Ranking by Inspiration: A Network Science Approach Livio Bioglio, Valentina Rho, Ruggero G. Pensa

Reflections on Reciprocity in Research Peter A. Flach

Robust Classification via MOM Minimization Guillaume Lecué, Matthieu Lerasle, Timothée Mathieu

Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding Di Wang, Xiangyu Guo, Shi Li, Jinhui Xu

Scalable Bayesian Preference Learning for Crowds Edwin Simpson, Iryna Gurevych

Skew Gaussian Processes for Classification Alessio Benavoli, Dario Azzimonti, Dario Piga

Skill-Based Curiosity for Intrinsically Motivated Reinforcement Learning Nicolas Bougie, Ryutaro Ichise

Spanning Attack: Reinforce Black-Box Attacks with Unlabeled Data Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang

Sparse Hierarchical Regression with Polynomials Dimitris Bertsimas, Bart P. G. Van Parys

Sum-Product Graphical Models Mattia Desana, Christoph Schnörr

Transfer Learning by Mapping and Revising Boosted Relational Dependency Networks Rodrigo Azevedo Santos, Aline Paes, Gerson Zaverucha

Unsupervised Representation Learning with Minimax Distance Measures Morteza Haghir Chehreghani

Using Error Decay Prediction to Overcome Practical Issues of Deep Active Learning for Named Entity Recognition Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, Andrew McCallum

Weak Approximation of Transformed Stochastic Gradient MCMC Soma Yokoi, Takuma Otsuka, Issei Sato