Table of Contents

• Deep Conditional Transformation ModelsPhilipp F. M. Baumann, Torsten Hothorn, David Rügamer. 3-18 [doi]
• Disentanglement and Local Directions of VarianceAlexander Rakowski, Christoph Lippert. 19-34 [doi]
• Neural Topic Models for Hierarchical Topic Detection and VisualizationDang-Pham, Tuan M. V. Le. 35-51 [doi]
• Semi-structured Document Annotation Using Entity and Relation TypesArpita Kundu, Subhasis Ghosh, Indrajit Bhattacharya. 52-68 [doi]
• Learning Disentangled Representations with the Wasserstein AutoencoderBenoit Gaujac, Ilya Feige, David Barber. 69-84 [doi]
• Which Minimizer Does My Neural Network Converge To?Manuel Nonnenmacher, David Reeb, Ingo Steinwart. 87-102 [doi]
• Information Interaction Profile of Choice AdoptionGaël Poux-Médard, Julien Velcin, Sabine Loudcher. 103-118 [doi]
• Joslim: Joint Widths and Weights Optimization for Slimmable Neural NetworksTing-Wu Chin, Ari S. Morcos, Diana Marculescu. 119-134 [doi]
• A Variance Controlled Stochastic Method with Biased Estimation for Faster Non-convex OptimizationJia Bi, Steve R. Gunn. 135-150 [doi]
• Very Fast Streaming Submodular Function MaximizationSebastian Buschjäger, Philipp-Jan Honysz, Lukas Pfahler, Katharina Morik. 151-166 [doi]
• 0-Based Network Sparsification via Dependency ModelingYang Li, Shihao Ji. 167-183 [doi]
• Variance Reduced Stochastic Proximal Algorithm for AUC MaximizationSoham Dan, Dushyant Sahoo. 184-199 [doi]
• Robust Regression via Model Based MethodsArmin Moharrer, Khashayar Kamran, Edmund Yeh, Stratis Ioannidis. 200-216 [doi]
• Black-Box Optimizer with Stochastic Implicit Natural GradientYueming Lyu, Ivor W. Tsang. 217-232 [doi]
• More General and Effective Model Compression via an Additive Combination of CompressionsYerlan Idelbayev, Miguel Á. Carreira-Perpiñán. 233-248 [doi]
• Hyper-parameter Optimization for Latent SpacesBruno Veloso, Luciano Caroprese, Matthias König, Sónia Teixeira, Giuseppe Manco 0001, Holger H. Hoos, João Gama 0001. 249-264 [doi]
• Bayesian Optimization with a Prior for the OptimumArtur L. F. Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter. 265-296 [doi]
• Rank Aggregation for Non-stationary Data StreamsEkhine Irurozki, Aritz Pérez, Jesus L. Lobo, Javier Del Ser. 297-313 [doi]
• Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR PredictionYun Yue, Yongchao Liu, Suo Tong, Minghao Li, Zhen Zhang, Chunyang Wen, Huanjun Bao, Lihong Gu, Jinjie Gu, Yixiang Mu. 314-329 [doi]
• Fast Conditional Network Compression Using Bayesian HyperNetworksPhuoc Nguyen, Truyen Tran 0001, Ky Le, Sunil Gupta 0001, Santu Rana, Dang Nguyen 0002, Trong Nguyen, Shannon Ryan, Svetha Venkatesh. 330-345 [doi]
• Active Learning in Gaussian Process State Space ModelHon Sum Alec Yu, Dingling Yao, Christoph Zimmer, Marc Toussaint, Duy Nguyen-Tuong. 346-361 [doi]
• Ensembling Shift Detectors: An Extensive Empirical EvaluationSimona Maggio, Léo Dreyfus-Schmidt. 362-377 [doi]
• Adaptive Learning Rate and Momentum for Training Deep Neural NetworksZhiyong Hao, Yixuan Jiang, Huihua Yu, Hsiao-Dong Chiang. 381-396 [doi]
• Attack Transferability Characterization for Adversarially Robust Multi-label ClassificationZhuo Yang, Yufei Han, Xiangliang Zhang 0001. 397-413 [doi]
• Differentiable Feature Selection, A Reparameterization ApproachJérémie Donà, Patrick Gallinari. 414-429 [doi]
• ATOM: Robustifying Out-of-Distribution Detection Using Outlier MiningJiefeng Chen, Yixuan Li, Xi Wu 0001, Yingyu Liang, Somesh Jha. 430-445 [doi]
• Robust Selection Stability Estimation in Correlated SpacesVictor Hamer, Pierre Dupont. 446-461 [doi]
• Gradient-Based Label Binning in Multi-label ClassificationMichael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier. 462-477 [doi]
• Joint Geometric and Topological Analysis of Hierarchical DatasetsLior Aloni, Omer Bobrowski, Ronen Talmon. 478-493 [doi]
• Reparameterized Sampling for Generative Adversarial NetworksYifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin. 494-509 [doi]
• Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message PassingKan Chen, Zhiqi Bu, Shiyun Xu. 510-526 [doi]
• Sparse Information Filter for Fast Gaussian Process RegressionLucas Kania, Manuel Schürch, Dario Azzimonti, Alessio Benavoli. 527-542 [doi]
• Bayesian Crowdsourcing with ConstraintsPanagiotis A. Traganitis, Georgios B. Giannakis. 543-559 [doi]
• VOGUE: Answer Verbalization Through Multi-Task LearningEndri Kacupaj, Shyamnath Premnadh, Kuldeep Singh 0001, Jens Lehmann 0001, Maria Maleshkova. 563-579 [doi]
• NA-Aware Machine Reading Comprehension for Document-Level Relation ExtractionZhenyu Zhang 0006, Bowen Yu 0002, Xiaobo Shu, Tingwen Liu. 580-595 [doi]
• Follow Your Path: A Progressive Method for Knowledge DistillationWenxian Shi, Yuxuan Song, Hao Zhou 0012, Bohan Li, Lei Li 0005. 596-611 [doi]
• TaxoRef: Embeddings Evaluation for AI-driven Taxonomy RefinementLorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani. 612-627 [doi]
• MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of GradientsChen Zhu, Yu Cheng 0001, Zhe Gan, Furong Huang, Jingjing Liu 0001, Tom Goldstein. 628-643 [doi]
• Augmenting Open-Domain Event Detection with Synthetic Data from GPT-2Amir Pouran Ben Veyseh, Minh Van Nguyen, Bonan Min, Thien Huu Nguyen. 644-660 [doi]
• Enhancing Summarization with Text Classification via Topic ConsistencyJingzhou Liu, Yiming Yang. 661-676 [doi]
• Transformers: "The End of History" for Natural Language Processing?Anton Chernyavskiy, Dmitry Ilvovsky, Preslav Nakov. 677-693 [doi]
• Subspace Clustering Based Analysis of Neural NetworksUday Singh Saini, Pravallika Devineni, Evangelos E. Papalexakis. 697-712 [doi]
• Invertible Manifold Learning for Dimension ReductionSiyuan Li, Haitao Lin, Zelin Zang, Lirong Wu, Jun Xia, Stan Z. Li. 713-728 [doi]
• Small-Vote Sample Selection for Label-Noise LearningYouze Xu, Yan Yan 0001, Jing-Hao Xue, Yang Lu 0009, Hanzi Wang. 729-744 [doi]
• Iterated Matrix ReorderingGauthier Van Vracem, Siegfried Nijssen. 745-761 [doi]
• Semi-supervised Semantic Visualization for Networked DocumentsDelvin Ce Zhang, Hady W. Lauw. 762-778 [doi]
• Self-supervised Multi-task Representation Learning for Sequential Medical ImagesNanqing Dong, Michael Kampffmeyer, Irina Voiculescu. 779-794 [doi]
• Label-Assisted Memory Autoencoder for Unsupervised Out-of-Distribution DetectionShuyi Zhang, Chao Pan, Liyan Song, Xiaoyu Wu, Zheng Hu, Ke Pei, Peter Tino, Xin Yao 0001. 795-810 [doi]
• Quantized Gromov-WassersteinSamir Chowdhury 0001, David Miller, Tom Needham. 811-827 [doi]