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🗄 Conference track papers are now available in PMLR Volume 129.
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Journal Track (6 papers)
- Binary classification with ambiguous training data
Naoyo Otani, Yosuke Otsubo, Tetsuya Koike, and Masashi Sugiyama - Boost Image Captioning with Knowledge Reasoning
Feicheng Huang, Zhixin Li, Haiyang Wei, Canlong Zhang, and Huifang Ma - Fast and Accurate Pseudoinverse with Sparse Matrix Reordering and Incremental Approach
Jinhong Jung and Lee Sael - Learning with Mitigating Random Consistency from the Accuracy Measure
Jieting Wang, Yuhua Qian, and Feijiang Li - Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding
Di Wang, Xiangyu Guo, Shi Li, and Jinhui Xu - Spanning attack: reinforce black-box attacks with unlabeled data
Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, and Yuan Jiang
Conference Track (54 papers)
- A Distance-Weighted Class-Homogeneous Neighbourhood Ratio for Algorithm Selection
Haofei Chen, Ya Liu, Japnit Kaur Ahuja, and Daren Ler - A foreground detection algorithm for Time-of-Flight cameras adapted dynamic integration time adjustment and multipath distortions
Detong Chen - A New Representation Learning Method for Individual Treatment Effect Estimation: Split Covariate Representation Network
Liu Qidong, Tian Feng, Ji Weihua, and Zheng Qinghua - A Novel Higher-order Weisfeiler-Lehman Graph Convolution
Clemens Damke, Vitalik Melnikov, and Eyke Hüllermeier - A One-step Approach to Covariate Shift Adaptation
Tianyi Zhang, Ikko Yamane, Nan Lu, and Masashi Sugiyama - A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning
Reza Refaei Afshar, Yingqian Zhang, Murat Firat, and Uzay Kaymak - AARM: Action Attention Recalibration Module for Action Recognition
Li Zhonghong, Yi Yang, She Ying, Song Jialun, and Wu Yukun - Atlas-aware ConvNet for Accurate yet Robust Anatomical Segmentation
Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, and Lei He - Bidirectional Dependency-Guided Attention for Relation Extraction
Xingchen Deng, Lei Zhang, Yixing Fan, Long Bai, Jiafeng Guo, and Pengfei Wang - Boosting-Based Reliable Model Reuse
Yao-Xiang Ding and Zhi-Hua Zhou - Bridging Ordinary-Label Learning and Complementary-Label Learning
Yasuhiro Katsura and Masato Uchida - CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow
Jia He, Feiyang Pan, Fuzhen Zhuang, and Qing He - Collaborative Exploration in Stochastic Multi-Player Bandits
Hiba Dakdouk, Raphaël Féraud, Nadège Varsier, and Patrick Maillé - Constrained Reinforcement Learning via Policy Splitting
Haoxian Chen, Henry Lam, Fengpei Li, and Amirhossein Meisami - Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization
Anas Barakat and Pascal Bianchi - Data-Dependent Conversion to a Compact Integer-Weighted Representation of a Weighted Voting Classifier
Mitsuki Maekawa, Atsuyoshi Nakamura, and Mineichi Kudo - Deep Dynamic Boosted Forest
Haixin Wang, Xingzhang Ren, Jinan Sun, Wei Ye, Long Chen, Muzhi Yu, and Shikun Zhang - Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning
Sourya Dey, Saikrishna C. Kanala, Keith M. Chugg, and Peter A. Beerel - DFQF: Data Free Quantization-aware Fine-tuning
Bowen Li, Kai Huang, Siang Chen, Dongliang Xiong, Haitian Jiang, and Luc Claesen - Disentangled Representations for Sequence Data using Information Bottleneck Principle
Masanori Yamada, Heecheol Kim, Kosuke Miyoshi, Tomoharu Iwata, and Hiroshi Yamakawa - Dual Learning: Theoretical Study and an Algorithmic Extension
Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, and Tie-Yan Liu - Efficient Attention Calibration Network for Real-Time Semantic Segmentation
Hengfeng Zha, Rui Liu, Dongsheng Zhou, Xin Yang, Qiang Zhang, and Xiaopeng Wei - Enhancing Topic Models by Incorporating Explicit and Implicit External Knowledge
Yang Hong, Xinhuai Tang, Tiancheng Tang, Yunlong Hu, and Jintai Tian - Exact Passive-Aggressive Algorithms for Multiclass Classification Using Bandit Feedbacks
Maanik Arora and Naresh Manwani - FIREPruning: Learning-based Filter Pruning for Convolutional Neural Network Compression
Fang, Yuchu and Li, Wenzhong and Zeng, Yao and Lu, Sanglu - Foolproof Cooperative Learning
Alexis Jacq, Julien Perolat, Matthieu Geist, and Olivier Pietquin - Geodesically-convex optimization for averaging partially observed covariance matrices
Florian Yger, Sylvain Chevallier, Quentin Barthélemy, and Suvrit Sra - Inferring Continuous Treatment Doses from Historical Data via Model-Based Entropy-Regularized Reinforcement Learning
Jianxun Wang, David Roberts, and Andinet Enquobahrie - Inverse Visual Question Answering with Multi-Level Attentions
Yaser Alwatter and Yuhong Guo - Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning
Paulo R d O Costa, Jason Rhuggenaath, Yingqian Zhang, and Alp Akcay - Learning Code Changes by Exploiting Bidirectional Converting Deviation
Jia-Wei Mi, Shu-Ting Shi, and Ming Li - Learning Dynamic Context Graph Embedding
Chuanchang Chen, Yubo Tao, and Hai Lin - Learning from Label Proportions with Consistency Regularization
Kuen-Han Tsai and Hsuan-Tien Lin - Learning Interpretable Models using Soft Integrity Constraints
Khaled Belahcène, Nataliya Sokolovska, Yann Chevaleyre, and Jean-Daniel Zucker - Localizing and Amortizing: Efficient Inference for Gaussian Processes
Linfeng Liu and Liping Liu - MetAL: Active Semi-Supervised Learning on Graphs via Meta-Learning
Kaushalya Madhawa and Tsuyoshi Murata - Monte-Carlo Graph Search: the Value of Merging Similar States
Edouard Leurent and Odalric-Ambrym Maillard - NENN: Incorporate Node and Edge Features in Graph Neural Networks
Yulei Yang and Dongsheng Li - Network Representation Learning Algorithm Based on Neighborhood Influence Sequence
Meng Liu, Ziwei Quan, and Yong Liu - Partially Observable Markov Decision Process Modelling for Assessing Hierarchies
Weipeng Huang, Guangyuan Piao, Raul Moreno, and Neil Hurley - Polytime Decomposition of Generalized Submodular Base Polytopes with Efficient Sampling
Aadirupa Saha - Proxy Network for Few Shot Learning
Bin Xiao, Chien-Liang Liu, and Wen-Hoar Hsaio - PSForest: Improving Deep Forest via Feature Pooling and Error Screening
Shiwen Ni and Hung-Yu Kao - Randomness Efficient Feature Hashing for Sparse Binary Data
Rameshwar Pratap, Karthik Revanuru, Anirudh Ravi, Raghav Kulkarni - Robust Deep Ordinal Regression under Label Noise
Bhanu Garg and Naresh Manwani - Robust Document Distance with Wasserstein-Fisher-Rao metric
Zihao Wang, Datong Zhou, Ming Yang, Yong Zhang, Chenglong Rao, and Hao Wu - Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis
Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr, and Eyke Hüllermeier - Scalable Calibration of Affinity Matrices from Incomplete Observations
Wenye Li - Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection
Nishma Laitonjam, Weipeng Huang, and Neil J. Hurley - Scaling up Simhash
Rameshwar Pratap, Anup Deshmukh, Pratheeksha Nair, and Anirudh Ravi - Semantic-Guided Shared Feature Alignment for Occluded Person Re-IDentification
Xuena Ren, Dongming Zhang, and Xiuguo Bao - Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning
Dung Nguyen, Svetha Venkatesh, Phuoc Nguyen, and Truyen Tran - Thompson Sampling for Unsupervised Sequential Selection
Arun Verma, Manjesh K Hanawal, and Nandyala Hemachandra - Towards Understanding and Improving the Transferability of Adversarial Examples in Deep Neural Networks
Lei Wu and Zhanxing Zhu