AAAI2019论文抢鲜看!48篇自然语言处理/计算机视觉/机器学习最新接受论文!

【导读】2019人工智能开年顶级会议AAAI的录取结果已出,投稿数量高达7745篇,录取率仅为16.2%。南京大学教授周志华和密歇根大学教授 Pascal Van Hentenryck是2019年AAAI程序主席专知整理了Twitter和arXiv以及作者主页公布的一些AAAI2019接受论文,共计48篇! 包括机器学习、自然语言处理、计算机视觉等类别,有些论文已经可以在arXiv找到!欢迎同学查看!



【机器学习篇】


  1. Federico Cerutti, Lance Kaplan, Angelika Kimmig, Murat Sensoy. Probabilistic Logic Programming with Beta-Distributed Random Variables.  In: AAAI (2019)

    https://arxiv.org/abs/1809.07888

  2.  Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Weinan Zhang, Lin Qiu, Yong Yu. Deep Recurrent Survival Analysis. In: AAAI (2019)

  3. https://arxiv.org/abs/1809.02403

  4. Guiding the One-to-one Mapping in CycleGAN via Optimal Transport, Z. Zhou, G. Lu, Y. Song, K. Ren, Y. Yu 

  5. On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation. A. Lissovoi, P.S. Oliveto and J.A.Warwicker.

  6. Freddy Lecue. et al. Human-in-the-Loop Feature Selection.

  7. Arnab Bhattacharyya. Minimum Intervention Cover of a Causal Graph

  8.  Daan Bloembergen, Davide Grossi, Martin Lackner. On Rational Delegations in Liquid Democracy.

    https://arxiv.org/abs/1802.08020

  9.  Bidisha Samanta, Abir De. Gourhari Jana, Pratim Kumar Chattaraj, Manuel Gomez Rodriguez. Designing Deep Generative Models for Molecular Graphs

  10. V. Roostapour, A. Neumann, F. Neumann, T. Friedrich: Pareto optimization for subset selection with dynamic cost constraints.

  11. T. Friedrich, A. Göbel, F. Neumann, F. Quinzan, R. Rothenberger: Greedy maximization of functions with bounded curvature under partition matroid constraints.

  12. T. Weise, Z. Wu, M. Wagner: An improved generic bet-and-run strategy with performance prediction for stochastic local search.

  13.  Lorenzo Severini. Coverage Centrality Maximization in Undirected Networks.

  14. Gissella Bejarano. Deep Latent Generative Models For Energy Disaggregation.

  15. Omer Ben-Porat, Gregory Goren, Itay Rosenberg, Moshe Tennenholtz:
    From Recommendation Systems to Facility Location Games

    https://arxiv.org/abs/1809.02931

  16. Convergence of Learning Dynamics in Information Retrieval Games Omer Ben-Porat, Itay Rosenberg, Moshe Tennenholtz

    https://arxiv.org/abs/1806.05359

  17.  Jiankai. ATP: Directed Graph Embedding with Asymmetric Transitivity.

  18. Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-MakingPhebe Vayanos

  19. Tanmoy Chakraborty. Gated Interleaved Multi-Task Composite State Sequencing: Learning to Daisy-Chain the Best Experts with GIRNet

  20. Junzhou Zhao, Shuo Shang, Xiangliang Zhang, Pinghui Wang, John C.S. Lui. “Submodular Optimization Over Streams with Inhomogeneous Decays”. Accepted for AAAI 2019. (CCF Rank A)


【计算机视觉篇】


  1. Ying Tai, Yicong Liang, Xiaoming Liu, Lei Duan, Jilin Li, Chengjie Wang, Feiyue Huang, Yu Chen. Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos. In: AAAI (2019)

    https://arxiv.org/abs/1811.00342

  2.  Manoj Acharya, Kushal Kafle, Christopher Kanan. TallyQA: Answering Complex Counting Questions.  In: AAAI (2019)

    https://arxiv.org/abs/1810.12440

    https://www.manojacharya.com/tallyqa.html

  3. Charles Ollion et al. BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection.

  4.  Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning Xin Wang, Jiawei Wu, Da Zhang, Yu Su, William Yang Wang AAAI 2019

  5.  F. Neumann, A. M. Sutton: Evolving solutions to community-structured satisfiability formulas.

  6. Laure Soulier. BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

  7. Toshihiko Yamasaki. Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing.


【自然语言处理篇】


  1. N Majumder, S Poria, D Hazarika, R Mihalcea, A Gelbukh, E Cambria.  DialogueRNN: An attentive RNN for emotion detection in conversations. In: AAAI (2019)

    https://arxiv.org/abs/1811.00405

  2. Farhad Bin Siddique, Dario Bertero, Pascale Fung. GlobalTrait: Personality Alignment of Multilingual Word Embeddings. In: AAAI (2019)

    https://arxiv.org/abs/1811.00240

  3. Maarten Sap, Ronan LeBras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin Choi. ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning.  In: AAAI (2019)

    https://arxiv.org/abs/1811.00146

  4. Sopan Khosla. Surveys without Questions: A Reinforcement Learning Approach.

  5. Quantifying Uncertainties in Natural Language Processing Tasks
    Yijun Xiao, William Yang Wang. AAAI 2019   

  6. Julien Tissier, Amaury Habrard, Christophe Gravier. Near-lossless Binarization of Word Embeddings

    https://arxiv.org/abs/1803.09065

  7. Mukundhan Srinivasan. Re-evaluating ADEM: A Deeper Look at Scoring Dialogue Responses.

  8. Yiming Cui. Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions.

  9.  julia kiseleva. Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning. 

  10. Md Kamruzzaman. Concept induction for description logic

  11. Xiaoyan Wang, Pavan Kapanipathi, Ryan Musa, Mo Yu, Kartik Talamadupula, Ibrahim Abdelaziz, Maria Chang, Achille Fokoue, Bassem Makni, Nicholas Mattei, Michael Witbrock: Improving Natural Language Inference Using External Knowledge in the Science Questions Domain

    https://arxiv.org/pdf/1809.05724.pdf

  12.  Najoung Kim, Kyle Rawlins, Benjamin Van Durme, Paul Smolensky:
    Predicting Argumenthood of English Preposition Phrases

    https://arxiv.org/abs/1809.07889

  13. Sebastian J. Mielke, Jason Eisner. Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model

    https://arxiv.org/abs/1804.08205

  14. Marek Rei. Jointly Learning to Label Sentences and Tokens.

  15.  Vasanth Sarathy. On Resolving Ambiguous Anaphoric Expressions in Imperative Discourse.

  16. DeepTileBars: Visualizing Term Distribution for Neural Information Retrieval" Zhiwen Tang and Grace Hui Yang

  17. Valerio Di Carlo. Building Temporal Word Embeddings with a Compass

  18.  Zhirui Zhang, Shuangzhi Wu, Shujie Liu, Mu Li, Ming Zhou, and Tong Xu, Regularizing Neural Machine Translation by Target-bidirectional Agreement, In Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, Hawaii, USA, 2019, Accepted.

  19. Hanqing Tao, Shiwei Tong, Hongke Zhao, Tong Xu, Binbin Jin, and Qi Liu, A Radical-aware Attention-based Model for Chinese Text Classification, In Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, Hawaii, USA, 2019, Accepted.



【其他】


  1. Yusuke Tanaka, Tomoharu Iwata, Toshiyuki Tanaka, Takeshi Kurashima, Maya Okawa, Hiroyuki Toda: Refining Coarse-grained Spatial Data using Auxiliary Spatial Data Sets with Various Granularities.

    https://arxiv.org/abs/1809.07952

  2. Incorporating Network Embedding into Markov Random Field for Better Community Detection

  3. Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Match. Jinfeng Rao, Wei Yang, Yuhao Zhang, Ferhan Ture, Jimmy Lin

    https://arxiv.org/abs/1805.08159


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