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10.1609/aaai.v34i01.7377 | A Spherical Convolution Approach for Learning Long Term Viewport Prediction in 360 Immersive Video | https://ojs.aaai.org/index.php/AAAI/article/view/7377 | https://ojs.aaai.org/index.php/AAAI/article/download/7377/7241 | [
"Chenglei Wu",
"Ruixiao Zhang",
"Zhi Wang",
"Lifeng Sun"
] | Viewport prediction for 360 video forecasts a viewer’s viewport when he/she watches a 360 video with a head-mounted display, which benefits many VR/AR applications such as 360 video streaming and mobile cloud VR. Existing studies based on planar convolutional neural network (CNN) suffer from the image distortion and sp... | main | AI and the Web | 10.1609/aaai.v34i01.7377 | 34 | 01 | 14003-14040 | official | null | null |
10.1609/aaai.v34i01.5367 | A Recurrent Model for Collective Entity Linking with Adaptive Features | https://ojs.aaai.org/index.php/AAAI/article/view/5367 | https://ojs.aaai.org/index.php/AAAI/article/download/5367/5223 | [
"Xiaoling Zhou",
"Yukai Miao",
"Wei Wang",
"Jianbin Qin"
] | The vast amount of web data enables us to build knowledge bases with unprecedented quality and coverage. Named Entity Disambiguation (NED) is an important task that automatically resolves ambiguous mentions in free text to correct target entries in the knowledge base. Traditional machine learning based methods for NED ... | main | AI and the Web | 10.1609/aaai.v34i01.5367 | 34 | 01 | 329-336 | official | null | null |
10.1609/aaai.v34i01.5366 | Table2Analysis: Modeling and Recommendation of Common Analysis Patterns for Multi-Dimensional Data | https://ojs.aaai.org/index.php/AAAI/article/view/5366 | https://ojs.aaai.org/index.php/AAAI/article/download/5366/5222 | [
"Mengyu Zhou",
"Wang Tao",
"Ji Pengxin",
"Han Shi",
"Zhang Dongmei"
] | Given a table of multi-dimensional data, what analyses would human create to extract information from it? From scientific exploration to business intelligence (BI), this is a key problem to solve towards automation of knowledge discovery and decision making. In this paper, we propose Table2Analysis to learn commonly co... | main | AI and the Web | 10.1609/aaai.v34i01.5366 | 34 | 01 | 320-328 | official | null | null |
10.1609/aaai.v34i01.5365 | Multi-Channel Reverse Dictionary Model | https://ojs.aaai.org/index.php/AAAI/article/view/5365 | https://ojs.aaai.org/index.php/AAAI/article/download/5365/5221 | [
"Lei Zhang",
"Fanchao Qi",
"Zhiyuan Liu",
"Yasheng Wang",
"Qun Liu",
"Maosong Sun"
] | A reverse dictionary takes the description of a target word as input and outputs the target word together with other words that match the description. Existing reverse dictionary methods cannot deal with highly variable input queries and low-frequency target words successfully. Inspired by the description-to-word infer... | main | AI and the Web | 10.1609/aaai.v34i01.5365 | 34 | 01 | 312-319 | official | 1912.08441 | title_snapshot |
10.1609/aaai.v34i01.5364 | An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos | https://ojs.aaai.org/index.php/AAAI/article/view/5364 | https://ojs.aaai.org/index.php/AAAI/article/download/5364/5220 | [
"Sicheng Zhao",
"Yunsheng Ma",
"Yang Gu",
"Jufeng Yang",
"Tengfei Xing",
"Pengfei Xu",
"Runbo Hu",
"Hua Chai",
"Kurt Keutzer"
] | Emotion recognition in user-generated videos plays an important role in human-centered computing. Existing methods mainly employ traditional two-stage shallow pipeline, i.e. extracting visual and/or audio features and training classifiers. In this paper, we propose to recognize video emotions in an end-to-end manner ba... | main | AI and the Web | 10.1609/aaai.v34i01.5364 | 34 | 01 | 303-311 | official | 2003.00832 | title_snapshot |
10.1609/aaai.v34i01.5363 | D2D-LSTM: LSTM-Based Path Prediction of Content Diffusion Tree in Device-to-Device Social Networks | https://ojs.aaai.org/index.php/AAAI/article/view/5363 | https://ojs.aaai.org/index.php/AAAI/article/download/5363/5219 | [
"Heng Zhang",
"Xiaofei Wang",
"Jiawen Chen",
"Chenyang Wang",
"Jianxin Li"
] | With the proliferation of mobile device users, the Device-to-Device (D2D) communication has ascended to the spotlight in social network for users to share and exchange enormous data. Different from classic online social network (OSN) like Twitter and Facebook, each single data file to be shared in the D2D social networ... | main | AI and the Web | 10.1609/aaai.v34i01.5363 | 34 | 01 | 295-302 | official | null | null |
10.1609/aaai.v34i01.5362 | Learning to Match on Graph for Fashion Compatibility Modeling | https://ojs.aaai.org/index.php/AAAI/article/view/5362 | https://ojs.aaai.org/index.php/AAAI/article/download/5362/5218 | [
"Xun Yang",
"Xiaoyu Du",
"Meng Wang"
] | Understanding the mix-and-match relationships between items receives increasing attention in the fashion industry. Existing methods have primarily learned visual compatibility from dyadic co-occurrence or co-purchase information of items to model the item-item matching interaction. Despite effectiveness, rich extra-con... | main | AI and the Web | 10.1609/aaai.v34i01.5362 | 34 | 01 | 287-294 | official | null | null |
10.1609/aaai.v34i01.5361 | Cross-Modal Attention Network for Temporal Inconsistent Audio-Visual Event Localization | https://ojs.aaai.org/index.php/AAAI/article/view/5361 | https://ojs.aaai.org/index.php/AAAI/article/download/5361/5217 | [
"Hanyu Xuan",
"Zhenyu Zhang",
"Shuo Chen",
"Jian Yang",
"Yan Yan"
] | In human multi-modality perception systems, the benefits of integrating auditory and visual information are extensive as they provide plenty supplementary cues for understanding the events. Despite some recent methods proposed for such application, they cannot deal with practical conditions with temporal inconsistency.... | main | AI and the Web | 10.1609/aaai.v34i01.5361 | 34 | 01 | 279-286 | official | null | null |
10.1609/aaai.v34i01.5349 | Incremental Fairness in Two-Sided Market Platforms: On Smoothly Updating Recommendations | https://ojs.aaai.org/index.php/AAAI/article/view/5349 | https://ojs.aaai.org/index.php/AAAI/article/download/5349/5205 | [
"Gourab K. Patro",
"Abhijnan Chakraborty",
"Niloy Ganguly",
"Krishna Gummadi"
] | Major online platforms today can be thought of as two-sided markets with producers and customers of goods and services. There have been concerns that over-emphasis on customer satisfaction by the platforms may affect the well-being of the producers. To counter such issues, few recent works have attempted to incorporate... | main | AI and the Web | 10.1609/aaai.v34i01.5349 | 34 | 01 | 181-188 | official | 1909.10005 | title_snapshot |
10.1609/aaai.v34i01.5348 | A Variational Point Process Model for Social Event Sequences | https://ojs.aaai.org/index.php/AAAI/article/view/5348 | https://ojs.aaai.org/index.php/AAAI/article/download/5348/5204 | [
"Zhen Pan",
"Zhenya Huang",
"Defu Lian",
"Enhong Chen"
] | Many events occur in real-world and social networks. Events are related to the past and there are patterns in the evolution of event sequences. Understanding the patterns can help us better predict the type and arriving time of the next event. In the literature, both feature-based approaches and generative approaches a... | main | AI and the Web | 10.1609/aaai.v34i01.5348 | 34 | 01 | 173-180 | official | null | null |
10.1609/aaai.v34i01.5350 | Towards Comprehensive Recommender Systems: Time-Aware Unified Recommendations Based on Listwise Ranking of Implicit Cross-Network Data | https://ojs.aaai.org/index.php/AAAI/article/view/5350 | https://ojs.aaai.org/index.php/AAAI/article/download/5350/5206 | [
"Dilruk Perera",
"Roger Zimmermann"
] | The abundance of information in web applications make recommendation essential for users as well as applications. Despite the effectiveness of existing recommender systems, we find two major limitations that reduce their overall performance: (1) inability to provide timely recommendations for both new and existing user... | main | AI and the Web | 10.1609/aaai.v34i01.5350 | 34 | 01 | 189-197 | official | 2008.13516 | title_judge |
10.1609/aaai.v34i01.5351 | Minimizing the Bag-of-Ngrams Difference for Non-Autoregressive Neural Machine Translation | https://ojs.aaai.org/index.php/AAAI/article/view/5351 | https://ojs.aaai.org/index.php/AAAI/article/download/5351/5207 | [
"Chenze Shao",
"Jinchao Zhang",
"Yang Feng",
"Fandong Meng",
"Jie Zhou"
] | Non-Autoregressive Neural Machine Translation (NAT) achieves significant decoding speedup through generating target words independently and simultaneously. However, in the context of non-autoregressive translation, the word-level cross-entropy loss cannot model the target-side sequential dependency properly, leading to... | main | AI and the Web | 10.1609/aaai.v34i01.5351 | 34 | 01 | 198-205 | official | 1911.09320 | title_snapshot |
10.1609/aaai.v34i01.5352 | PEIA: Personality and Emotion Integrated Attentive Model for Music Recommendation on Social Media Platforms | https://ojs.aaai.org/index.php/AAAI/article/view/5352 | https://ojs.aaai.org/index.php/AAAI/article/download/5352/5208 | [
"Tiancheng Shen",
"Jia Jia",
"Yan Li",
"Yihui Ma",
"Yaohua Bu",
"Hanjie Wang",
"Bo Chen",
"Tat-Seng Chua",
"Wendy Hall"
] | With the rapid expansion of digital music formats, it's indispensable to recommend users with their favorite music. For music recommendation, users' personality and emotion greatly affect their music preference, respectively in a long-term and short-term manner, while rich social media data provides effective feedback ... | main | AI and the Web | 10.1609/aaai.v34i01.5352 | 34 | 01 | 206-213 | official | null | null |
10.1609/aaai.v34i01.5353 | Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/5353 | https://ojs.aaai.org/index.php/AAAI/article/download/5353/5209 | [
"Ke Sun",
"Tieyun Qian",
"Tong Chen",
"Yile Liang",
"Quoc Viet Hung Nguyen",
"Hongzhi Yin"
] | Point-of-Interest (POI) recommendation has been a trending research topic as it generates personalized suggestions on facilities for users from a large number of candidate venues. Since users' check-in records can be viewed as a long sequence, methods based on recurrent neural networks (RNNs) have recently shown promis... | main | AI and the Web | 10.1609/aaai.v34i01.5353 | 34 | 01 | 214-221 | official | null | null |
10.1609/aaai.v34i01.5354 | Knowledge Graph Alignment Network with Gated Multi-Hop Neighborhood Aggregation | https://ojs.aaai.org/index.php/AAAI/article/view/5354 | https://ojs.aaai.org/index.php/AAAI/article/download/5354/5210 | [
"Zequn Sun",
"Chengming Wang",
"Wei Hu",
"Muhao Chen",
"Jian Dai",
"Wei Zhang",
"Yuzhong Qu"
] | Graph neural networks (GNNs) have emerged as a powerful paradigm for embedding-based entity alignment due to their capability of identifying isomorphic subgraphs. However, in real knowledge graphs (KGs), the counterpart entities usually have non-isomorphic neighborhood structures, which easily causes GNNs to yield diff... | main | AI and the Web | 10.1609/aaai.v34i01.5354 | 34 | 01 | 222-229 | official | 1911.08936 | title_snapshot |
10.1609/aaai.v34i01.5355 | Learning with Unsure Responses | https://ojs.aaai.org/index.php/AAAI/article/view/5355 | https://ojs.aaai.org/index.php/AAAI/article/download/5355/5211 | [
"Kunihiro Takeoka",
"Yuyang Dong",
"Masafumi Oyamada"
] | Many annotation systems provide to add an unsure option in the labels, because the annotators have different expertise, and they may not have enough confidence to choose a label for some assigned instances. However, all the existing approaches only learn the labels with a clear class name and ignore the unsure response... | main | AI and the Web | 10.1609/aaai.v34i01.5355 | 34 | 01 | 230-237 | official | null | null |
10.1609/aaai.v34i01.5356 | Author Name Disambiguation on Heterogeneous Information Network with Adversarial Representation Learning | https://ojs.aaai.org/index.php/AAAI/article/view/5356 | https://ojs.aaai.org/index.php/AAAI/article/download/5356/5212 | [
"Haiwen Wang",
"Ruijie Wan",
"Chuan Wen",
"Shuhao Li",
"Yuting Jia",
"Weinan Zhang",
"Xinbing Wang"
] | Author name ambiguity causes inadequacy and inconvenience in academic information retrieval, which raises the necessity of author name disambiguation (AND). Existing AND methods can be divided into two categories: the models focusing on content information to distinguish whether two papers are written by the same autho... | main | AI and the Web | 10.1609/aaai.v34i01.5356 | 34 | 01 | 238-245 | official | 2002.09803 | title_snapshot |
10.1609/aaai.v34i01.5357 | Social Influence Does Matter: User Action Prediction for In-Feed Advertising | https://ojs.aaai.org/index.php/AAAI/article/view/5357 | https://ojs.aaai.org/index.php/AAAI/article/download/5357/5213 | [
"Hongyang Wang",
"Qingfei Meng",
"Ju Fan",
"Yuchen Li",
"Laizhong Cui",
"Xiaoman Zhao",
"Chong Peng",
"Gong Chen",
"Xiaoyong Du"
] | Social in-feed advertising delivers ads that seamlessly fit inside a user’s feed, and allows users to engage in social actions (likes or comments) with the ads. Many businesses pay higher attention to “engagement marketing” that maximizes social actions, as social actions can effectively promote brand awareness. This p... | main | AI and the Web | 10.1609/aaai.v34i01.5357 | 34 | 01 | 246-253 | official | null | null |
10.1609/aaai.v34i01.5358 | Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction | https://ojs.aaai.org/index.php/AAAI/article/view/5358 | https://ojs.aaai.org/index.php/AAAI/article/download/5358/5214 | [
"Haozhe Wu",
"Zhiyuan Hu",
"Jia Jia",
"Yaohua Bu",
"Xiangnan He",
"Tat-Seng Chua"
] | Online Social Networks (OSNs) evolve through two pervasive behaviors: follow and unfollow, which respectively signify relationship creation and relationship dissolution. Researches on social network evolution mainly focus on the follow behavior, while the unfollow behavior has largely been ignored. Mining unfollow beha... | main | AI and the Web | 10.1609/aaai.v34i01.5358 | 34 | 01 | 254-261 | official | 1911.07156 | title_snapshot |
10.1609/aaai.v34i01.5359 | Who Likes What? — SplitLBI in Exploring Preferential Diversity of Ratings | https://ojs.aaai.org/index.php/AAAI/article/view/5359 | https://ojs.aaai.org/index.php/AAAI/article/download/5359/5215 | [
"Qianqian Xu",
"Jiechao Xiong",
"Zhiyong Yang",
"Xiaochun Cao",
"Qingming Huang",
"Yuan Yao"
] | In recent years, learning user preferences has received significant attention. A shortcoming of existing learning to rank work lies in that they do not take into account the multi-level hierarchies from social choice to individuals. In this paper, we propose a multi-level model which learns both the common preference o... | main | AI and the Web | 10.1609/aaai.v34i01.5359 | 34 | 01 | 262-269 | official | null | null |
10.1609/aaai.v34i01.5360 | Multi-Feature Discrete Collaborative Filtering for Fast Cold-Start Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/5360 | https://ojs.aaai.org/index.php/AAAI/article/download/5360/5216 | [
"Yang Xu",
"Lei Zhu",
"Zhiyong Cheng",
"Jingjing Li",
"Jiande Sun"
] | Hashing is an effective technique to address the large-scale recommendation problem, due to its high computation and storage efficiency on calculating the user preferences on items. However, existing hashing-based recommendation methods still suffer from two important problems: 1) Their recommendation process mainly re... | main | AI and the Web | 10.1609/aaai.v34i01.5360 | 34 | 01 | 270-278 | official | 2003.10719 | title_snapshot |
10.1609/aaai.v34i01.5347 | Modality to Modality Translation: An Adversarial Representation Learning and Graph Fusion Network for Multimodal Fusion | https://ojs.aaai.org/index.php/AAAI/article/view/5347 | https://ojs.aaai.org/index.php/AAAI/article/download/5347/5203 | [
"Sijie Mai",
"Haifeng Hu",
"Songlong Xing"
] | Learning joint embedding space for various modalities is of vital importance for multimodal fusion. Mainstream modality fusion approaches fail to achieve this goal, leaving a modality gap which heavily affects cross-modal fusion. In this paper, we propose a novel adversarial encoder-decoder-classifier framework to lear... | main | AI and the Web | 10.1609/aaai.v34i01.5347 | 34 | 01 | 164-172 | official | 1911.07848 | title_snapshot |
10.1609/aaai.v34i01.5346 | Deep Match to Rank Model for Personalized Click-Through Rate Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/5346 | https://ojs.aaai.org/index.php/AAAI/article/download/5346/5202 | [
"Ze Lyu",
"Yu Dong",
"Chengfu Huo",
"Weijun Ren"
] | Click-through rate (CTR) prediction is a core task in the field of recommender system and many other applications. For CTR prediction model, personalization is the key to improve the performance and enhance the user experience. Recently, several models are proposed to extract user interest from user behavior data which... | main | AI and the Web | 10.1609/aaai.v34i01.5346 | 34 | 01 | 156-163 | official | null | null |
10.1609/aaai.v34i01.5345 | Type-Aware Anchor Link Prediction across Heterogeneous Networks Based on Graph Attention Network | https://ojs.aaai.org/index.php/AAAI/article/view/5345 | https://ojs.aaai.org/index.php/AAAI/article/download/5345/5201 | [
"Xiaoxue Li",
"Yanmin Shang",
"Yanan Cao",
"Yangxi Li",
"Jianlong Tan",
"Yanbing Liu"
] | Anchor Link Prediction (ALP) across heterogeneous networks plays a pivotal role in inter-network applications. The difficulty of anchor link prediction in heterogeneous networks lies in how to consider the factors affecting nodes alignment comprehensively. In recent years, predicting anchor links based on network embed... | main | AI and the Web | 10.1609/aaai.v34i01.5345 | 34 | 01 | 147-155 | official | null | null |
10.1609/aaai.v34i01.5344 | Understanding and Improving Proximity Graph Based Maximum Inner Product Search | https://ojs.aaai.org/index.php/AAAI/article/view/5344 | https://ojs.aaai.org/index.php/AAAI/article/download/5344/5200 | [
"Jie Liu",
"Xiao Yan",
"Xinyan Dai",
"Zhirong Li",
"James Cheng",
"Ming-Chang Yang"
] | The inner-product navigable small world graph (ip-NSW) represents the state-of-the-art method for approximate maximum inner product search (MIPS) and it can achieve an order of magnitude speedup over the fastest baseline. However, to date it is still unclear where its exceptional performance comes from. In this paper, ... | main | AI and the Web | 10.1609/aaai.v34i01.5344 | 34 | 01 | 139-146 | official | 1909.13459 | title_snapshot |
10.1609/aaai.v34i01.5343 | True Nonlinear Dynamics from Incomplete Networks | https://ojs.aaai.org/index.php/AAAI/article/view/5343 | https://ojs.aaai.org/index.php/AAAI/article/download/5343/5199 | [
"Chunheng Jiang",
"Jianxi Gao",
"Malik Magdon-Ismail"
] | We study nonlinear dynamics on complex networks. Each vertex i has a state xi which evolves according to a networked dynamics to a steady-state xi*. We develop fundamental tools to learn the true steady-state of a small part of the network, without knowing the full network. A naive approach and the current state-of-the... | main | AI and the Web | 10.1609/aaai.v34i01.5343 | 34 | 01 | 131-138 | official | 2001.06722 | title_snapshot |
10.1609/aaai.v34i01.5342 | Functionality Discovery and Prediction of Physical Objects | https://ojs.aaai.org/index.php/AAAI/article/view/5342 | https://ojs.aaai.org/index.php/AAAI/article/download/5342/5198 | [
"Lei Ji",
"Botian Shi",
"Xianglin Guo",
"Xilin Chen"
] | Functionality is a fundamental attribute of an object which indicates the capability to be used to perform specific actions. It is critical to empower robots the functionality knowledge in discovering appropriate objects for a task e.g. cut cake using knife. Existing research works have focused on understanding object ... | main | AI and the Web | 10.1609/aaai.v34i01.5342 | 34 | 01 | 123-130 | official | null | null |
10.1609/aaai.v34i01.5341 | Cross-Lingual Pre-Training Based Transfer for Zero-Shot Neural Machine Translation | https://ojs.aaai.org/index.php/AAAI/article/view/5341 | https://ojs.aaai.org/index.php/AAAI/article/download/5341/5197 | [
"Baijun Ji",
"Zhirui Zhang",
"Xiangyu Duan",
"Min Zhang",
"Boxing Chen",
"Weihua Luo"
] | Transfer learning between different language pairs has shown its effectiveness for Neural Machine Translation (NMT) in low-resource scenario. However, existing transfer methods involving a common target language are far from success in the extreme scenario of zero-shot translation, due to the language space mismatch pr... | main | AI and the Web | 10.1609/aaai.v34i01.5341 | 34 | 01 | 115-122 | official | 1912.01214 | title_snapshot |
10.1609/aaai.v34i01.5328 | MultiSumm: Towards a Unified Model for Multi-Lingual Abstractive Summarization | https://ojs.aaai.org/index.php/AAAI/article/view/5328 | https://ojs.aaai.org/index.php/AAAI/article/download/5328/5184 | [
"Yue Cao",
"Xiaojun Wan",
"Jinge Yao",
"Dian Yu"
] | Automatic text summarization aims at producing a shorter version of the input text that conveys the most important information. However, multi-lingual text summarization, where the goal is to process texts in multiple languages and output summaries in the corresponding languages with a single model, has been rarely stu... | main | AI and the Web | 10.1609/aaai.v34i01.5328 | 34 | 01 | 11-18 | official | null | null |
10.1609/aaai.v34i01.5327 | Balancing Spreads of Influence in a Social Network | https://ojs.aaai.org/index.php/AAAI/article/view/5327 | https://ojs.aaai.org/index.php/AAAI/article/download/5327/5183 | [
"Ruben Becker",
"Federico Corò",
"Gianlorenzo D'Angelo",
"Hugo Gilbert"
] | The personalization of our news consumption on social media has a tendency to reinforce our pre-existing beliefs instead of balancing our opinions. To tackle this issue, Garimella et al. (NIPS'17) modeled the spread of these viewpoints, also called campaigns, using the independent cascade model introduced by Kempe, Kle... | main | AI and the Web | 10.1609/aaai.v34i01.5327 | 34 | 01 | 3-10 | official | 1906.00074 | title_snapshot |
10.1609/aaai.v34i01.5329 | Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/5329 | https://ojs.aaai.org/index.php/AAAI/article/download/5329/5185 | [
"Chong Chen",
"Min Zhang",
"Yongfeng Zhang",
"Weizhi Ma",
"Yiqun Liu",
"Shaoping Ma"
] | Recent studies on recommendation have largely focused on exploring state-of-the-art neural networks to improve the expressiveness of models, while typically apply the Negative Sampling (NS) strategy for efficient learning. Despite effectiveness, two important issues have not been well-considered in existing methods: 1)... | main | AI and the Web | 10.1609/aaai.v34i01.5329 | 34 | 01 | 19-26 | official | null | null |
10.1609/aaai.v34i01.5330 | Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach | https://ojs.aaai.org/index.php/AAAI/article/view/5330 | https://ojs.aaai.org/index.php/AAAI/article/download/5330/5186 | [
"Lei Chen",
"Le Wu",
"Richang Hong",
"Kun Zhang",
"Meng Wang"
] | Graph Convolutional Networks~(GCNs) are state-of-the-art graph based representation learning models by iteratively stacking multiple layers of convolution aggregation operations and non-linear activation operations. Recently, in Collaborative Filtering~(CF) based Recommender Systems~(RS), by treating the user-item inte... | main | AI and the Web | 10.1609/aaai.v34i01.5330 | 34 | 01 | 27-34 | official | 2001.10167 | title_snapshot |
10.1609/aaai.v34i01.5331 | Question-Driven Purchasing Propensity Analysis for Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/5331 | https://ojs.aaai.org/index.php/AAAI/article/download/5331/5187 | [
"Long Chen",
"Ziyu Guan",
"Qibin Xu",
"Qiong Zhang",
"Huan Sun",
"Guangyue Lu",
"Deng Cai"
] | Merchants of e-commerce Websites expect recommender systems to entice more consumption which is highly correlated with the customers' purchasing propensity. However, most existing recommender systems focus on customers' general preference rather than purchasing propensity often governed by instant demands which we deem... | main | AI and the Web | 10.1609/aaai.v34i01.5331 | 34 | 01 | 35-42 | official | null | null |
10.1609/aaai.v34i01.5332 | Gradient Method for Continuous Influence Maximization with Budget-Saving Considerations | https://ojs.aaai.org/index.php/AAAI/article/view/5332 | https://ojs.aaai.org/index.php/AAAI/article/download/5332/5188 | [
"Wei Chen",
"Weizhong Zhang",
"Haoyu Zhao"
] | Continuous influence maximization (CIM) generalizes the original influence maximization by incorporating general marketing strategies: a marketing strategy mix is a vector x = (x1, …, xd) such that for each node v in a social network, v could be activated as a seed of diffusion with probability hv(x), where hv is a str... | main | AI and the Web | 10.1609/aaai.v34i01.5332 | 34 | 01 | 43-50 | official | 1911.09100 | title_snapshot |
10.1609/aaai.v34i01.5333 | Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search | https://ojs.aaai.org/index.php/AAAI/article/view/5333 | https://ojs.aaai.org/index.php/AAAI/article/download/5333/5189 | [
"Xinyan Dai",
"Xiao Yan",
"Kelvin K. W. Ng",
"Jiu Liu",
"James Cheng"
] | Vector quantization (VQ) techniques are widely used in similarity search for data compression, computation acceleration and etc. Originally designed for Euclidean distance, existing VQ techniques (e.g., PQ, AQ) explicitly or implicitly minimize the quantization error. In this paper, we present a new angle to analyze th... | main | AI and the Web | 10.1609/aaai.v34i01.5333 | 34 | 01 | 51-58 | official | 1911.04654 | title_snapshot |
10.1609/aaai.v34i01.5334 | Modeling Fluency and Faithfulness for Diverse Neural Machine Translation | https://ojs.aaai.org/index.php/AAAI/article/view/5334 | https://ojs.aaai.org/index.php/AAAI/article/download/5334/5190 | [
"Yang Feng",
"Wanying Xie",
"Shuhao Gu",
"Chenze Shao",
"Wen Zhang",
"Zhengxin Yang",
"Dong Yu"
] | Neural machine translation models usually adopt the teacher forcing strategy for training which requires the predicted sequence matches ground truth word by word and forces the probability of each prediction to approach a 0-1 distribution. However, the strategy casts all the portion of the distribution to the ground tr... | main | AI and the Web | 10.1609/aaai.v34i01.5334 | 34 | 01 | 59-66 | official | 1912.00178 | title_snapshot |
10.1609/aaai.v34i01.5335 | Leveraging Title-Abstract Attentive Semantics for Paper Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/5335 | https://ojs.aaai.org/index.php/AAAI/article/download/5335/5191 | [
"Guibing Guo",
"Bowei Chen",
"Xiaoyan Zhang",
"Zhirong Liu",
"Zhenhua Dong",
"Xiuqiang He"
] | Paper recommendation is a research topic to provide users with personalized papers of interest. However, most existing approaches equally treat title and abstract as the input to learn the representation of a paper, ignoring their semantic relationship. In this paper, we regard the abstract as a sequence of sentences, ... | main | AI and the Web | 10.1609/aaai.v34i01.5335 | 34 | 01 | 67-74 | official | null | null |
10.1609/aaai.v34i01.5336 | Preserving Ordinal Consensus: Towards Feature Selection for Unlabeled Data | https://ojs.aaai.org/index.php/AAAI/article/view/5336 | https://ojs.aaai.org/index.php/AAAI/article/download/5336/5192 | [
"Jun Guo",
"Heng Chang",
"Wenwu Zhu"
] | To better pre-process unlabeled data, most existing feature selection methods remove redundant and noisy information by exploring some intrinsic structures embedded in samples. However, these unsupervised studies focus too much on the relations among samples, totally neglecting the feature-level geometric information. ... | main | AI and the Web | 10.1609/aaai.v34i01.5336 | 34 | 01 | 75-82 | official | null | null |
10.1609/aaai.v34i01.5337 | An Attentional Recurrent Neural Network for Personalized Next Location Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/5337 | https://ojs.aaai.org/index.php/AAAI/article/download/5337/5193 | [
"Qing Guo",
"Zhu Sun",
"Jie Zhang",
"Yin-Leng Theng"
] | Most existing studies on next location recommendation propose to model the sequential regularity of check-in sequences, but suffer from the severe data sparsity issue where most locations have fewer than five following locations. To this end, we propose an Attentional Recurrent Neural Network (ARNN) to jointly model bo... | main | AI and the Web | 10.1609/aaai.v34i01.5337 | 34 | 01 | 83-90 | official | null | null |
10.1609/aaai.v34i01.5338 | Re-Attention for Visual Question Answering | https://ojs.aaai.org/index.php/AAAI/article/view/5338 | https://ojs.aaai.org/index.php/AAAI/article/download/5338/5194 | [
"Wenya Guo",
"Ying Zhang",
"Xiaoping Wu",
"Jufeng Yang",
"Xiangrui Cai",
"Xiaojie Yuan"
] | Visual Question Answering~(VQA) requires a simultaneous understanding of images and questions. Existing methods achieve well performance by focusing on both key objects in images and key words in questions. However, the answer also contains rich information which can help to better describe the image and generate more ... | main | AI and the Web | 10.1609/aaai.v34i01.5338 | 34 | 01 | 91-98 | official | null | null |
10.1609/aaai.v34i01.5339 | Semi-Supervised Multi-Modal Learning with Balanced Spectral Decomposition | https://ojs.aaai.org/index.php/AAAI/article/view/5339 | https://ojs.aaai.org/index.php/AAAI/article/download/5339/5195 | [
"Peng Hu",
"Hongyuan Zhu",
"Xi Peng",
"Jie Lin"
] | Cross-modal retrieval aims to retrieve the relevant samples across different modalities, of which the key problem is how to model the correlations among different modalities while narrowing the large heterogeneous gap. In this paper, we propose a Semi-supervised Multimodal Learning Network method (SMLN) which correlate... | main | AI and the Web | 10.1609/aaai.v34i01.5339 | 34 | 01 | 99-106 | official | null | null |
10.1609/aaai.v34i01.5340 | MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection | https://ojs.aaai.org/index.php/AAAI/article/view/5340 | https://ojs.aaai.org/index.php/AAAI/article/download/5340/5196 | [
"Ling Huang",
"Hong-Yang Chao",
"Quangqiang Xie"
] | In the past few years, higher-order community detection has drawn an increasing amount of attention. Compared with the lower-order approaches that rely on the connectivity pattern of individual nodes and edges, the higher-order approaches discover communities by leveraging the higher-order connectivity pattern via cons... | main | AI and the Web | 10.1609/aaai.v34i01.5340 | 34 | 01 | 107-114 | official | null | null |
10.1609/aaai.v34i01.5482 | MixedAD: A Scalable Algorithm for Detecting Mixed Anomalies in Attributed Graphs | https://ojs.aaai.org/index.php/AAAI/article/view/5482 | https://ojs.aaai.org/index.php/AAAI/article/download/5482/5338 | [
"Mengxiao Zhu",
"Haogang Zhu"
] | Attributed graphs, where nodes are associated with a rich set of attributes, have been widely used in various domains. Among all the nodes, those with patterns that deviate significantly from others are of particular interest. There are mainly two challenges for anomaly detection. For one thing, we often encounter larg... | main | Applications | 10.1609/aaai.v34i01.5482 | 34 | 01 | 1274-1281 | official | null | null |
10.1609/aaai.v34i01.5467 | MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control | https://ojs.aaai.org/index.php/AAAI/article/view/5467 | https://ojs.aaai.org/index.php/AAAI/article/download/5467/5323 | [
"Xinshi Zang",
"Huaxiu Yao",
"Guanjie Zheng",
"Nan Xu",
"Kai Xu",
"Zhenhui Li"
] | Using reinforcement learning for traffic signal control has attracted increasing interests recently. Various value-based reinforcement learning methods have been proposed to deal with this classical transportation problem and achieved better performances compared with traditional transportation methods. However, curren... | main | Applications | 10.1609/aaai.v34i01.5467 | 34 | 01 | 1153-1160 | official | null | null |
10.1609/aaai.v34i01.5462 | Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States | https://ojs.aaai.org/index.php/AAAI/article/view/5462 | https://ojs.aaai.org/index.php/AAAI/article/download/5462/5318 | [
"Yunan Ye",
"Hengzhi Pei",
"Boxin Wang",
"Pin-Yu Chen",
"Yada Zhu",
"Ju Xiao",
"Bo Li"
] | Portfolio management (PM) is a fundamental financial planning task that aims to achieve investment goals such as maximal profits or minimal risks. Its decision process involves continuous derivation of valuable information from various data sources and sequential decision optimization, which is a prospective research d... | main | Applications | 10.1609/aaai.v34i01.5462 | 34 | 01 | 1112-1119 | official | 2002.05780 | title_snapshot |
10.1609/aaai.v34i01.5463 | Attention Based Data Hiding with Generative Adversarial Networks | https://ojs.aaai.org/index.php/AAAI/article/view/5463 | https://ojs.aaai.org/index.php/AAAI/article/download/5463/5319 | [
"Chong Yu"
] | Recently, the generative adversarial network is the hotspot in research and industrial areas. Its application on data generation is the most common usage. In this paper, we propose the novel end-to-end framework to extend its application to data hiding area. The discriminative model simulates the detection process, whi... | main | Applications | 10.1609/aaai.v34i01.5463 | 34 | 01 | 1120-1128 | official | null | null |
10.1609/aaai.v34i01.5464 | AirNet: A Calibration Model for Low-Cost Air Monitoring Sensors Using Dual Sequence Encoder Networks | https://ojs.aaai.org/index.php/AAAI/article/view/5464 | https://ojs.aaai.org/index.php/AAAI/article/download/5464/5320 | [
"Haomin Yu",
"Qingyong Li",
"Yangli-ao Geng",
"Yingjun Zhang",
"Zhi Wei"
] | Air pollution monitoring has attracted much attention in recent years. However, accurate and high-resolution monitoring of atmospheric pollution remains challenging. There are two types of devices for air pollution monitoring, i.e., static stations and mobile stations. Static stations can provide accurate pollution mea... | main | Applications | 10.1609/aaai.v34i01.5464 | 34 | 01 | 1129-1136 | official | null | null |
10.1609/aaai.v34i01.5465 | Towards Hands-Free Visual Dialog Interactive Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/5465 | https://ojs.aaai.org/index.php/AAAI/article/download/5465/5321 | [
"Tong Yu",
"Yilin Shen",
"Hongxia Jin"
] | With the recent advances of multimodal interactive recommendations, the users are able to express their preference by natural language feedback to the item images, to find the desired items. However, the existing systems either retrieve only one item or require the user to specify (e.g., by click or touch) the commente... | main | Applications | 10.1609/aaai.v34i01.5465 | 34 | 01 | 1137-1144 | official | null | null |
10.1609/aaai.v34i01.5466 | Order Matters: Semantic-Aware Neural Networks for Binary Code Similarity Detection | https://ojs.aaai.org/index.php/AAAI/article/view/5466 | https://ojs.aaai.org/index.php/AAAI/article/download/5466/5322 | [
"Zeping Yu",
"Rui Cao",
"Qiyi Tang",
"Sen Nie",
"Junzhou Huang",
"Shi Wu"
] | Binary code similarity detection, whose goal is to detect similar binary functions without having access to the source code, is an essential task in computer security. Traditional methods usually use graph matching algorithms, which are slow and inaccurate. Recently, neural network-based approaches have made great achi... | main | Applications | 10.1609/aaai.v34i01.5466 | 34 | 01 | 1145-1152 | official | null | null |
10.1609/aaai.v34i01.5468 | Geometry-Constrained Car Recognition Using a 3D Perspective Network | https://ojs.aaai.org/index.php/AAAI/article/view/5468 | https://ojs.aaai.org/index.php/AAAI/article/download/5468/5324 | [
"Zeng Rui",
"Ge Zongyuan",
"Denman Simon",
"Sridharan Sridha",
"Fookes Clinton"
] | We present a novel learning framework for vehicle recognition from a single RGB image. Unlike existing methods which only use attention mechanisms to locate 2D discriminative information, our work learns a novel 3D perspective feature representation of a vehicle, which is then fused with 2D appearance feature to predic... | main | Applications | 10.1609/aaai.v34i01.5468 | 34 | 01 | 1161-1168 | official | 1903.07916 | title_snapshot |
10.1609/aaai.v34i01.5469 | Generating Adversarial Examples for Holding Robustness of Source Code Processing Models | https://ojs.aaai.org/index.php/AAAI/article/view/5469 | https://ojs.aaai.org/index.php/AAAI/article/download/5469/5325 | [
"Huangzhao Zhang",
"Zhuo Li",
"Ge Li",
"Lei Ma",
"Yang Liu",
"Zhi Jin"
] | Automated processing, analysis, and generation of source code are among the key activities in software and system lifecycle. To this end, while deep learning (DL) exhibits a certain level of capability in handling these tasks, the current state-of-the-art DL models still suffer from non-robust issues and can be easily ... | main | Applications | 10.1609/aaai.v34i01.5469 | 34 | 01 | 1169-1176 | official | null | null |
10.1609/aaai.v34i01.5470 | Spatio-Temporal Graph Structure Learning for Traffic Forecasting | https://ojs.aaai.org/index.php/AAAI/article/view/5470 | https://ojs.aaai.org/index.php/AAAI/article/download/5470/5326 | [
"Qi Zhang",
"Jianlong Chang",
"Gaofeng Meng",
"Shiming Xiang",
"Chunhong Pan"
] | As an indispensable part in Intelligent Traffic System (ITS), the task of traffic forecasting inherently subjects to the following three challenging aspects. First, traffic data are physically associated with road networks, and thus should be formatted as traffic graphs rather than regular grid-like tensors. Second, tr... | main | Applications | 10.1609/aaai.v34i01.5470 | 34 | 01 | 1177-1185 | official | null | null |
10.1609/aaai.v34i01.5471 | Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/5471 | https://ojs.aaai.org/index.php/AAAI/article/download/5471/5327 | [
"Weijia Zhang",
"Hao Liu",
"Yanchi Liu",
"Jingbo Zhou",
"Hui Xiong"
] | The ability to predict city-wide parking availability is crucial for the successful development of Parking Guidance and Information (PGI) systems. Indeed, the effective prediction of city-wide parking availability can improve parking efficiency, help urban planning, and ultimately alleviate city congestion. However, it... | main | Applications | 10.1609/aaai.v34i01.5471 | 34 | 01 | 1186-1193 | official | 1911.10516 | title_snapshot |
10.1609/aaai.v34i01.5473 | A Novel Learning Framework for Sampling-Based Motion Planning in Autonomous Driving | https://ojs.aaai.org/index.php/AAAI/article/view/5473 | https://ojs.aaai.org/index.php/AAAI/article/download/5473/5329 | [
"Yifan Zhang",
"Jinghuai Zhang",
"Jindi Zhang",
"Jianping Wang",
"Kejie Lu",
"Jeff Hong"
] | Sampling-based motion planning (SBMP) is a major trajectory planning approach in autonomous driving given its high efficiency in practice. As the core of SBMP schemes, sampling strategy holds the key to whether a smooth and collision-free trajectory can be found in real-time. Although some bias sampling strategies have... | main | Applications | 10.1609/aaai.v34i01.5473 | 34 | 01 | 1202-1209 | official | null | null |
10.1609/aaai.v34i01.5481 | Deep Reservoir Computing Meets 5G MIMO-OFDM Systems in Symbol Detection | https://ojs.aaai.org/index.php/AAAI/article/view/5481 | https://ojs.aaai.org/index.php/AAAI/article/download/5481/5337 | [
"Zhou Zhou",
"Lingjia Liu",
"Vikram Chandrasekhar",
"Jianzhong Zhang",
"Yang Yi"
] | Conventional reservoir computing (RC) is a shallow recurrent neural network (RNN) with fixed high dimensional hidden dynamics and one trainable output layer. It has the nice feature of requiring limited training which is critical for certain applications where training data is extremely limited and costly to obtain. In... | main | Applications | 10.1609/aaai.v34i01.5481 | 34 | 01 | 1266-1273 | official | null | null |
10.1609/aaai.v34i01.5480 | RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework | https://ojs.aaai.org/index.php/AAAI/article/view/5480 | https://ojs.aaai.org/index.php/AAAI/article/download/5480/5336 | [
"Zhengyang Zhou",
"Yang Wang",
"Xike Xie",
"Lianliang Chen",
"Hengchang Liu"
] | Real-time traffic accident forecasting is increasingly important for public safety and urban management (e.g., real-time safe route planning and emergency response deployment). Previous works on accident forecasting are often performed on hour levels, utilizing existed neural networks with static region-wise correlatio... | main | Applications | 10.1609/aaai.v34i01.5480 | 34 | 01 | 1258-1265 | official | 2003.00819 | title_snapshot |
10.1609/aaai.v34i01.5479 | Iteratively Questioning and Answering for Interpretable Legal Judgment Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/5479 | https://ojs.aaai.org/index.php/AAAI/article/download/5479/5335 | [
"Haoxi Zhong",
"Yuzhong Wang",
"Cunchao Tu",
"Tianyang Zhang",
"Zhiyuan Liu",
"Maosong Sun"
] | Legal Judgment Prediction (LJP) aims to predict judgment results according to the facts of cases. In recent years, LJP has drawn increasing attention rapidly from both academia and the legal industry, as it can provide references for legal practitioners and is expected to promote judicial justice. However, the research... | main | Applications | 10.1609/aaai.v34i01.5479 | 34 | 01 | 1250-1257 | official | null | null |
10.1609/aaai.v34i01.5478 | Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach | https://ojs.aaai.org/index.php/AAAI/article/view/5478 | https://ojs.aaai.org/index.php/AAAI/article/download/5478/5334 | [
"Yu Zheng",
"Bowei Chen",
"Timothy M. Hospedales",
"Yongxin Yang"
] | Partial (replication) index tracking is a popular passive investment strategy. It aims to replicate the performance of a given index by constructing a tracking portfolio which contains some constituents of the index. The tracking error optimisation is quadratic and NP-hard when taking the ℓ0 constraint into account so ... | main | Applications | 10.1609/aaai.v34i01.5478 | 34 | 01 | 1242-1249 | official | 1911.05052 | title_snapshot |
10.1609/aaai.v34i01.5477 | GMAN: A Graph Multi-Attention Network for Traffic Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/5477 | https://ojs.aaai.org/index.php/AAAI/article/download/5477/5333 | [
"Chuanpan Zheng",
"Xiaoliang Fan",
"Cheng Wang",
"Jianzhong Qi"
] | Long-term traffic prediction is highly challenging due to the complexity of traffic systems and the constantly changing nature of many impacting factors. In this paper, we focus on the spatio-temporal factors, and propose a graph multi-attention network (GMAN) to predict traffic conditions for time steps ahead at diffe... | main | Applications | 10.1609/aaai.v34i01.5477 | 34 | 01 | 1234-1241 | official | 1911.08415 | title_snapshot |
10.1609/aaai.v34i01.5476 | MaskGEC: Improving Neural Grammatical Error Correction via Dynamic Masking | https://ojs.aaai.org/index.php/AAAI/article/view/5476 | https://ojs.aaai.org/index.php/AAAI/article/download/5476/5332 | [
"Zewei Zhao",
"Houfeng Wang"
] | Grammatical error correction (GEC) is a promising natural language processing (NLP) application, whose goal is to change the sentences with grammatical errors into the correct ones. Neural machine translation (NMT) approaches have been widely applied to this translation-like task. However, such methods need a fairly la... | main | Applications | 10.1609/aaai.v34i01.5476 | 34 | 01 | 1226-1233 | official | null | null |
10.1609/aaai.v34i01.5475 | OF-MSRN: Optical Flow-Auxiliary Multi-Task Regression Network for Direct Quantitative Measurement, Segmentation and Motion Estimation | https://ojs.aaai.org/index.php/AAAI/article/view/5475 | https://ojs.aaai.org/index.php/AAAI/article/download/5475/5331 | [
"Chengqian Zhao",
"Cheng Feng",
"Dengwang Li",
"Shuo Li"
] | Comprehensively analyzing the carotid artery is critically significant to diagnosing and treating cardiovascular diseases. The object of this work is to simultaneously achieve direct quantitative measurement and automated segmentation of the lumen diameter and intima-media thickness as well as the motion estimation of ... | main | Applications | 10.1609/aaai.v34i01.5475 | 34 | 01 | 1218-1225 | official | null | null |
10.1609/aaai.v34i01.5474 | Dynamic Malware Analysis with Feature Engineering and Feature Learning | https://ojs.aaai.org/index.php/AAAI/article/view/5474 | https://ojs.aaai.org/index.php/AAAI/article/download/5474/5330 | [
"Zhaoqi Zhang",
"Panpan Qi",
"Wei Wang"
] | Dynamic malware analysis executes the program in an isolated environment and monitors its run-time behaviour (e.g. system API calls) for malware detection. This technique has been proven to be effective against various code obfuscation techniques and newly released (“zero-day”) malware. However, existing works typicall... | main | Applications | 10.1609/aaai.v34i01.5474 | 34 | 01 | 1210-1217 | official | 1907.07352 | title_snapshot |
10.1609/aaai.v34i01.5472 | Shoreline: Data-Driven Threshold Estimation of Online Reserves of Cryptocurrency Trading Platforms | https://ojs.aaai.org/index.php/AAAI/article/view/5472 | https://ojs.aaai.org/index.php/AAAI/article/download/5472/5328 | [
"Xitong Zhang",
"He Zhu",
"Jiayu Zhou"
] | With the proliferation of blockchain projects and applications, cryptocurrency exchanges, which provides exchange services among different types of cryptocurrencies, become pivotal platforms that allow customers to trade digital assets on different blockchains. Because of the anonymity and trustlessness nature of crypt... | main | Applications | 10.1609/aaai.v34i01.5472 | 34 | 01 | 1194-1201 | official | null | null |
10.1609/aaai.v34i01.5461 | Instance-Wise Dynamic Sensor Selection for Human Activity Recognition | https://ojs.aaai.org/index.php/AAAI/article/view/5461 | https://ojs.aaai.org/index.php/AAAI/article/download/5461/5317 | [
"Xiaodong Yang",
"Yiqiang Chen",
"Hanchao Yu",
"Yingwei Zhang",
"Wang Lu",
"Ruizhe Sun"
] | Human Activity Recognition (HAR) is an important application of smart wearable/mobile systems for many human-centric problems such as healthcare. The multi-sensor synchronous measurement has shown better performance for HAR than a single sensor. However, the multi-sensor setting increases the costs of data transmission... | main | Applications | 10.1609/aaai.v34i01.5461 | 34 | 01 | 1104-1111 | official | null | null |
10.1609/aaai.v34i01.5441 | Finding Minimum-Weight Link-Disjoint Paths with a Few Common Nodes | https://ojs.aaai.org/index.php/AAAI/article/view/5441 | https://ojs.aaai.org/index.php/AAAI/article/download/5441/5297 | [
"Binglin Tao",
"Mingyu Xiao",
"Jingyang Zhao"
] | Network survivability has drawn certain interest in network optimization. However, the demand for full protection of a network is usually too restrictive. To overcome the limitation of geographical environments and to save network resources, we turn to establish backup networks allowing a few common nodes. It comes out... | main | Applications | 10.1609/aaai.v34i01.5441 | 34 | 01 | 938-945 | official | null | null |
10.1609/aaai.v34i01.5442 | Finding Needles in a Moving Haystack: Prioritizing Alerts with Adversarial Reinforcement Learning | https://ojs.aaai.org/index.php/AAAI/article/view/5442 | https://ojs.aaai.org/index.php/AAAI/article/download/5442/5298 | [
"Liang Tong",
"Aron Laszka",
"Chao Yan",
"Ning Zhang",
"Yevgeniy Vorobeychik"
] | Detection of malicious behavior is a fundamental problem in security. One of the major challenges in using detection systems in practice is in dealing with an overwhelming number of alerts that are triggered by normal behavior (the so-called false positives), obscuring alerts resulting from actual malicious activities.... | main | Applications | 10.1609/aaai.v34i01.5442 | 34 | 01 | 946-953 | official | 1906.08805 | title_snapshot |
10.1609/aaai.v34i01.5443 | Robust Adversarial Objects against Deep Learning Models | https://ojs.aaai.org/index.php/AAAI/article/view/5443 | https://ojs.aaai.org/index.php/AAAI/article/download/5443/5299 | [
"Tzungyu Tsai",
"Kaichen Yang",
"Tsung-Yi Ho",
"Yier Jin"
] | Previous work has shown that Deep Neural Networks (DNNs), including those currently in use in many fields, are extremely vulnerable to maliciously crafted inputs, known as adversarial examples. Despite extensive and thorough research of adversarial examples in many areas, adversarial 3D data, such as point clouds, rema... | main | Applications | 10.1609/aaai.v34i01.5443 | 34 | 01 | 954-962 | official | null | null |
10.1609/aaai.v34i01.5444 | OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting | https://ojs.aaai.org/index.php/AAAI/article/view/5444 | https://ojs.aaai.org/index.php/AAAI/article/download/5444/5300 | [
"Ding Wang",
"Boyang Liu",
"Pang-Ning Tan",
"Lifeng Luo"
] | Hurricanes are powerful tropical cyclones with sustained wind speeds ranging from at least 74 mph (for category 1 storms) to more than 157 mph (for category 5 storms). Accurate prediction of the storm tracks is essential for hurricane preparedness and mitigation of storm impacts. In this paper, we cast the hurricane tr... | main | Applications | 10.1609/aaai.v34i01.5444 | 34 | 01 | 963-970 | official | null | null |
10.1609/aaai.v34i01.5445 | Incorporating Expert-Based Investment Opinion Signals in Stock Prediction: A Deep Learning Framework | https://ojs.aaai.org/index.php/AAAI/article/view/5445 | https://ojs.aaai.org/index.php/AAAI/article/download/5445/5301 | [
"Heyuan Wang",
"Tengjiao Wang",
"Yi Li"
] | Investment messages published on social media platforms are highly valuable for stock prediction. Most previous work regards overall message sentiments as forecast indicators and relies on shallow features (bag-of-words, noun phrases, etc.) to determine the investment opinion signals. These methods neither capture the ... | main | Applications | 10.1609/aaai.v34i01.5445 | 34 | 01 | 971-978 | official | null | null |
10.1609/aaai.v34i01.5446 | Graph-Driven Generative Models for Heterogeneous Multi-Task Learning | https://ojs.aaai.org/index.php/AAAI/article/view/5446 | https://ojs.aaai.org/index.php/AAAI/article/download/5446/5302 | [
"Wenlin Wang",
"Hongteng Xu",
"Zhe Gan",
"Bai Li",
"Guoyin Wang",
"Liqun Chen",
"Qian Yang",
"Wenqi Wang",
"Lawrence Carin"
] | We propose a novel graph-driven generative model, that unifies multiple heterogeneous learning tasks into the same framework. The proposed model is based on the fact that heterogeneous learning tasks, which correspond to different generative processes, often rely on data with a shared graph structure. Accordingly, our ... | main | Applications | 10.1609/aaai.v34i01.5446 | 34 | 01 | 979-988 | official | 1911.08709 | title_snapshot |
10.1609/aaai.v34i01.5447 | Topic Enhanced Sentiment Spreading Model in Social Networks Considering User Interest | https://ojs.aaai.org/index.php/AAAI/article/view/5447 | https://ojs.aaai.org/index.php/AAAI/article/download/5447/5303 | [
"Xiaobao Wang",
"Di Jin",
"Katarzyna Musial",
"Jianwu Dang"
] | Emotion is a complex emotional state, which can affect our physiology and psychology and lead to behavior changes. The spreading process of emotions in the text-based social networks is referred to as sentiment spreading. In this paper, we study an interesting problem of sentiment spreading in social networks. In parti... | main | Applications | 10.1609/aaai.v34i01.5447 | 34 | 01 | 989-996 | official | null | null |
10.1609/aaai.v34i01.5448 | HDK: Toward High-Performance Deep-Learning-Based Kirchhoff Analysis | https://ojs.aaai.org/index.php/AAAI/article/view/5448 | https://ojs.aaai.org/index.php/AAAI/article/download/5448/5304 | [
"Xinying Wang",
"Olamide Timothy Tawose",
"Feng Yan",
"Dongfang Zhao"
] | The Kirchhoff law is one of the most widely used physical laws in many engineering principles, e.g., biomedical engineering, electrical engineering, and computer engineering. One challenge of applying the Kirchhoff law to real-world applications at scale lies in the high, if not prohibitive, computational cost to solve... | main | Applications | 10.1609/aaai.v34i01.5448 | 34 | 01 | 997-1004 | official | null | null |
10.1609/aaai.v34i01.5449 | Actor Critic Deep Reinforcement Learning for Neural Malware Control | https://ojs.aaai.org/index.php/AAAI/article/view/5449 | https://ojs.aaai.org/index.php/AAAI/article/download/5449/5305 | [
"Yu Wang",
"Jack Stokes",
"Mady Marinescu"
] | In addition to using signatures, antimalware products also detect malicious attacks by evaluating unknown files in an emulated environment, i.e. sandbox, prior to execution on a computer's native operating system. During emulation, a file cannot be scanned indefinitely, and antimalware engines often set the number of i... | main | Applications | 10.1609/aaai.v34i01.5449 | 34 | 01 | 1005-1012 | official | null | null |
10.1609/aaai.v34i01.5450 | Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding | https://ojs.aaai.org/index.php/AAAI/article/view/5450 | https://ojs.aaai.org/index.php/AAAI/article/download/5450/5306 | [
"Zhecheng Wang",
"Haoyuan Li",
"Ram Rajagopal"
] | Understanding intrinsic patterns and predicting spatiotemporal characteristics of cities require a comprehensive representation of urban neighborhoods. Existing works relied on either inter- or intra-region connectivities to generate neighborhood representations but failed to fully utilize the informative yet heterogen... | main | Applications | 10.1609/aaai.v34i01.5450 | 34 | 01 | 1013-1020 | official | 2001.11101 | title_snapshot |
10.1609/aaai.v34i01.5451 | Hiding in Multilayer Networks | https://ojs.aaai.org/index.php/AAAI/article/view/5451 | https://ojs.aaai.org/index.php/AAAI/article/download/5451/5307 | [
"Marcin Waniek",
"Tomasz Michalak",
"Talal Rahwan"
] | Multilayer networks allow for modeling complex relationships, where individuals are embedded in multiple social networks at the same time. Given the ubiquity of such relationships, these networks have been increasingly gaining attention in the literature. This paper presents the first analysis of the robustness of cent... | main | Applications | 10.1609/aaai.v34i01.5451 | 34 | 01 | 1021-1028 | official | 1911.05947 | title_snapshot |
10.1609/aaai.v34i01.5453 | DeepDualMapper: A Gated Fusion Network for Automatic Map Extraction Using Aerial Images and Trajectories | https://ojs.aaai.org/index.php/AAAI/article/view/5453 | https://ojs.aaai.org/index.php/AAAI/article/download/5453/5309 | [
"Hao Wu",
"Hanyuan Zhang",
"Xinyu Zhang",
"Weiwei Sun",
"Baihua Zheng",
"Yuning Jiang"
] | Automatic map extraction is of great importance to urban computing and location-based services. Aerial image and GPS trajectory data refer to two different data sources that could be leveraged to generate the map, although they carry different types of information. Most previous works on data fusion between aerial imag... | main | Applications | 10.1609/aaai.v34i01.5453 | 34 | 01 | 1037-1045 | official | 2002.06832 | title_snapshot |
10.1609/aaai.v34i01.5454 | Accelerating and Improving AlphaZero Using Population Based Training | https://ojs.aaai.org/index.php/AAAI/article/view/5454 | https://ojs.aaai.org/index.php/AAAI/article/download/5454/5310 | [
"Ti-Rong Wu",
"Ting-Han Wei",
"I-Chen Wu"
] | AlphaZero has been very successful in many games. Unfortunately, it still consumes a huge amount of computing resources, the majority of which is spent in self-play. Hyperparameter tuning exacerbates the training cost since each hyperparameter configuration requires its own time to train one run, during which it will g... | main | Applications | 10.1609/aaai.v34i01.5454 | 34 | 01 | 1046-1053 | official | 2003.06212 | title_snapshot |
10.1609/aaai.v34i01.5455 | Graph Convolutional Networks with Markov Random Field Reasoning for Social Spammer Detection | https://ojs.aaai.org/index.php/AAAI/article/view/5455 | https://ojs.aaai.org/index.php/AAAI/article/download/5455/5311 | [
"Yongji Wu",
"Defu Lian",
"Yiheng Xu",
"Le Wu",
"Enhong Chen"
] | The recent growth of social networking platforms also led to the emergence of social spammers, who overwhelm legitimate users with unwanted content. The existing social spammer detection methods can be characterized into two categories: features based ones and propagation-based ones. Features based methods mainly rely ... | main | Applications | 10.1609/aaai.v34i01.5455 | 34 | 01 | 1054-1061 | official | null | null |
10.1609/aaai.v34i01.5456 | Generative Adversarial Regularized Mutual Information Policy Gradient Framework for Automatic Diagnosis | https://ojs.aaai.org/index.php/AAAI/article/view/5456 | https://ojs.aaai.org/index.php/AAAI/article/download/5456/5312 | [
"Yuan Xia",
"Jingbo Zhou",
"Zhenhui Shi",
"Chao Lu",
"Haifeng Huang"
] | Automatic diagnosis systems have attracted increasing attention in recent years. The reinforcement learning (RL) is an attractive technique for building an automatic diagnosis system due to its advantages for handling sequential decision making problem. However, the RL method still cannot achieve good enough prediction... | main | Applications | 10.1609/aaai.v34i01.5456 | 34 | 01 | 1062-1069 | official | null | null |
10.1609/aaai.v34i01.5457 | Generate (Non-Software) Bugs to Fool Classifiers | https://ojs.aaai.org/index.php/AAAI/article/view/5457 | https://ojs.aaai.org/index.php/AAAI/article/download/5457/5313 | [
"Hiromu Yakura",
"Youhei Akimoto",
"Jun Sakuma"
] | In adversarial attacks intended to confound deep learning models, most studies have focused on limiting the magnitude of the modification so that humans do not notice the attack. On the other hand, during an attack against autonomous cars, for example, most drivers would not find it strange if a small insect image were... | main | Applications | 10.1609/aaai.v34i01.5457 | 34 | 01 | 1070-1078 | official | 1911.08644 | title_snapshot |
10.1609/aaai.v34i01.5458 | Fairness-Aware Demand Prediction for New Mobility | https://ojs.aaai.org/index.php/AAAI/article/view/5458 | https://ojs.aaai.org/index.php/AAAI/article/download/5458/5314 | [
"An Yan",
"Bill Howe"
] | Emerging transportation modes, including car-sharing, bike-sharing, and ride-hailing, are transforming urban mobility yet have been shown to reinforce socioeconomic inequity. These services rely on accurate demand prediction, but the demand data on which these models are trained reflect biases around demographics, soci... | main | Applications | 10.1609/aaai.v34i01.5458 | 34 | 01 | 1079-1087 | official | null | null |
10.1609/aaai.v34i01.5459 | Beyond Digital Domain: Fooling Deep Learning Based Recognition System in Physical World | https://ojs.aaai.org/index.php/AAAI/article/view/5459 | https://ojs.aaai.org/index.php/AAAI/article/download/5459/5315 | [
"Kaichen Yang",
"Tzungyu Tsai",
"Honggang Yu",
"Tsung-Yi Ho",
"Yier Jin"
] | Adversarial examples that can fool deep neural network (DNN) models in computer vision present a growing threat. The current methods of launching adversarial attacks concentrate on attacking image classifiers by adding noise to digital inputs. The problem of attacking object detection models and adversarial attacks in ... | main | Applications | 10.1609/aaai.v34i01.5459 | 34 | 01 | 1088-1095 | official | null | null |
10.1609/aaai.v34i01.5460 | Scalable and Generalizable Social Bot Detection through Data Selection | https://ojs.aaai.org/index.php/AAAI/article/view/5460 | https://ojs.aaai.org/index.php/AAAI/article/download/5460/5316 | [
"Kai-Cheng Yang",
"Onur Varol",
"Pik-Mai Hui",
"Filippo Menczer"
] | Efficient and reliable social bot classification is crucial for detecting information manipulation on social media. Despite rapid development, state-of-the-art bot detection models still face generalization and scalability challenges, which greatly limit their applications. In this paper we propose a framework that use... | main | Applications | 10.1609/aaai.v34i01.5460 | 34 | 01 | 1096-1103 | official | 1911.09179 | title_snapshot |
10.1609/aaai.v34i01.5437 | Effective Decoding in Graph Auto-Encoder Using Triadic Closure | https://ojs.aaai.org/index.php/AAAI/article/view/5437 | https://ojs.aaai.org/index.php/AAAI/article/download/5437/5293 | [
"Han Shi",
"Haozheng Fan",
"James T. Kwok"
] | The (variational) graph auto-encoder and its variants have been popularly used for representation learning on graph-structured data. While the encoder is often a powerful graph convolutional network, the decoder reconstructs the graph structure by only considering two nodes at a time, thus ignoring possible interaction... | main | Applications | 10.1609/aaai.v34i01.5437 | 34 | 01 | 906-913 | official | 1911.11322 | title_snapshot |
10.1609/aaai.v34i01.5440 | DATA-GRU: Dual-Attention Time-Aware Gated Recurrent Unit for Irregular Multivariate Time Series | https://ojs.aaai.org/index.php/AAAI/article/view/5440 | https://ojs.aaai.org/index.php/AAAI/article/download/5440/5296 | [
"Qingxiong Tan",
"Mang Ye",
"Baoyao Yang",
"Siqi Liu",
"Andy Jinhua Ma",
"Terry Cheuk-Fung Yip",
"Grace Lai-Hung Wong",
"PongChi Yuen"
] | Due to the discrepancy of diseases and symptoms, patients usually visit hospitals irregularly and different physiological variables are examined at each visit, producing large amounts of irregular multivariate time series (IMTS) data with missing values and varying intervals. Existing methods process IMTS into regular ... | main | Applications | 10.1609/aaai.v34i01.5440 | 34 | 01 | 930-937 | official | null | null |
10.1609/aaai.v34i01.5439 | Continuous Multiagent Control Using Collective Behavior Entropy for Large-Scale Home Energy Management | https://ojs.aaai.org/index.php/AAAI/article/view/5439 | https://ojs.aaai.org/index.php/AAAI/article/download/5439/5295 | [
"Jianwen Sun",
"Yan Zheng",
"Jianye Hao",
"Zhaopeng Meng",
"Yang Liu"
] | With the increasing popularity of electric vehicles, distributed energy generation and storage facilities in smart grid systems, an efficient Demand-Side Management (DSM) is urgent for energy savings and peak loads reduction. Traditional DSM works focusing on optimizing the energy activities for a single household can ... | main | Applications | 10.1609/aaai.v34i01.5439 | 34 | 01 | 922-929 | official | 2005.10000 | title_snapshot |
10.1609/aaai.v34i01.5438 | Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting | https://ojs.aaai.org/index.php/AAAI/article/view/5438 | https://ojs.aaai.org/index.php/AAAI/article/download/5438/5294 | [
"Chao Song",
"Youfang Lin",
"Shengnan Guo",
"Huaiyu Wan"
] | Spatial-temporal network data forecasting is of great importance in a huge amount of applications for traffic management and urban planning. However, the underlying complex spatial-temporal correlations and heterogeneities make this problem challenging. Existing methods usually use separate components to capture spatia... | main | Applications | 10.1609/aaai.v34i01.5438 | 34 | 01 | 914-921 | official | null | null |
10.1609/aaai.v34i01.5436 | Spatial Classification with Limited Observations Based on Physics-Aware Structural Constraint | https://ojs.aaai.org/index.php/AAAI/article/view/5436 | https://ojs.aaai.org/index.php/AAAI/article/download/5436/5292 | [
"Arpan Man Sainju",
"Wenchong He",
"Zhe Jiang",
"Da Yan"
] | Spatial classification with limited feature observations has been a challenging problem in machine learning. The problem exists in applications where only a subset of sensors are deployed at certain regions or partial responses are collected in field surveys. Existing research mostly focuses on addressing incomplete or... | main | Applications | 10.1609/aaai.v34i01.5436 | 34 | 01 | 898-905 | official | 2009.01072 | title_snapshot |
10.1609/aaai.v34i01.5421 | Towards Cross-Modality Medical Image Segmentation with Online Mutual Knowledge Distillation | https://ojs.aaai.org/index.php/AAAI/article/view/5421 | https://ojs.aaai.org/index.php/AAAI/article/download/5421/5277 | [
"Kang Li",
"Lequan Yu",
"Shujun Wang",
"Pheng-Ann Heng"
] | The success of deep convolutional neural networks is partially attributed to the massive amount of annotated training data. However, in practice, medical data annotations are usually expensive and time-consuming to be obtained. Considering multi-modality data with the same anatomic structures are widely available in cl... | main | Applications | 10.1609/aaai.v34i01.5421 | 34 | 01 | 775-783 | official | 2010.01532 | title_snapshot |
10.1609/aaai.v34i01.5422 | Privacy-Preserving Gradient Boosting Decision Trees | https://ojs.aaai.org/index.php/AAAI/article/view/5422 | https://ojs.aaai.org/index.php/AAAI/article/download/5422/5278 | [
"Qinbin Li",
"Zhaomin Wu",
"Zeyi Wen",
"Bingsheng He"
] | The Gradient Boosting Decision Tree (GBDT) is a popular machine learning model for various tasks in recent years. In this paper, we study how to improve model accuracy of GBDT while preserving the strong guarantee of differential privacy. Sensitivity and privacy budget are two key design aspects for the effectiveness o... | main | Applications | 10.1609/aaai.v34i01.5422 | 34 | 01 | 784-791 | official | 1911.04209 | title_snapshot |
10.1609/aaai.v34i01.5423 | MRI Reconstruction with Interpretable Pixel-Wise Operations Using Reinforcement Learning | https://ojs.aaai.org/index.php/AAAI/article/view/5423 | https://ojs.aaai.org/index.php/AAAI/article/download/5423/5279 | [
"Wentian Li",
"Xidong Feng",
"Haotian An",
"Xiang Yao Ng",
"Yu-Jin Zhang"
] | Compressed sensing magnetic resonance imaging (CS-MRI) is a technique aimed at accelerating the data acquisition of MRI. While down-sampling in k-space proportionally reduces the data acquisition time, it results in images corrupted by aliasing artifacts and blur. To reconstruct images from the down-sampled k-space, re... | main | Applications | 10.1609/aaai.v34i01.5423 | 34 | 01 | 792-799 | official | null | null |
10.1609/aaai.v34i01.5424 | PSENet: Psoriasis Severity Evaluation Network | https://ojs.aaai.org/index.php/AAAI/article/view/5424 | https://ojs.aaai.org/index.php/AAAI/article/download/5424/5280 | [
"Yi Li",
"Zhe Wu",
"Shuang Zhao",
"Xian Wu",
"Yehong Kuang",
"Yangtian Yan",
"Shen Ge",
"Kai Wang",
"Wei Fan",
"Xiang Chen",
"Yong Wang"
] | Psoriasis is a chronic skin disease which affects hundreds of millions of people around the world. This disease cannot be fully cured and requires lifelong caring. If the deterioration of Psoriasis is not detected and properly treated in time, it could cause serious complications or even lead to a life threat. Therefor... | main | Applications | 10.1609/aaai.v34i01.5424 | 34 | 01 | 800-807 | official | null | null |
10.1609/aaai.v34i01.5425 | Learning Geo-Contextual Embeddings for Commuting Flow Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/5425 | https://ojs.aaai.org/index.php/AAAI/article/download/5425/5281 | [
"Zhicheng Liu",
"Fabio Miranda",
"Weiting Xiong",
"Junyan Yang",
"Qiao Wang",
"Claudio Silva"
] | Predicting commuting flows based on infrastructure and land-use information is critical for urban planning and public policy development. However, it is a challenging task given the complex patterns of commuting flows. Conventional models, such as gravity model, are mainly derived from physics principles and limited by... | main | Applications | 10.1609/aaai.v34i01.5425 | 34 | 01 | 808-816 | official | 2005.01690 | title_snapshot |
10.1609/aaai.v34i01.5426 | Learning Multi-Modal Biomarker Representations via Globally Aligned Longitudinal Enrichments | https://ojs.aaai.org/index.php/AAAI/article/view/5426 | https://ojs.aaai.org/index.php/AAAI/article/download/5426/5282 | [
"Lyujian Lu",
"Saad Elbeleidy",
"Lauren Zoe Baker",
"Hua Wang"
] | Alzheimer's Disease (AD) is a chronic neurodegenerative disease that severely impacts patients' thinking, memory and behavior. To aid automatic AD diagnoses, many longitudinal learning models have been proposed to predict clinical outcomes and/or disease status, which, though, often fail to consider missing temporal ph... | main | Applications | 10.1609/aaai.v34i01.5426 | 34 | 01 | 817-824 | official | null | null |
10.1609/aaai.v34i01.5427 | AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration | https://ojs.aaai.org/index.php/AAAI/article/view/5427 | https://ojs.aaai.org/index.php/AAAI/article/download/5427/5283 | [
"Liantao Ma",
"Junyi Gao",
"Yasha Wang",
"Chaohe Zhang",
"Jiangtao Wang",
"Wenjie Ruan",
"Wen Tang",
"Xin Gao",
"Xinyu Ma"
] | Deep learning-based health status representation learning and clinical prediction have raised much research interest in recent years. Existing models have shown superior performance, but there are still several major issues that have not been fully taken into consideration. First, the historical variation pattern of th... | main | Applications | 10.1609/aaai.v34i01.5427 | 34 | 01 | 825-832 | official | 1911.12205 | title_snapshot |
10.1609/aaai.v34i01.5428 | ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context | https://ojs.aaai.org/index.php/AAAI/article/view/5428 | https://ojs.aaai.org/index.php/AAAI/article/download/5428/5284 | [
"Liantao Ma",
"Chaohe Zhang",
"Yasha Wang",
"Wenjie Ruan",
"Jiangtao Wang",
"Wen Tang",
"Xinyu Ma",
"Xin Gao",
"Junyi Gao"
] | Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics. Most deep learning-based solutions for EMR analysis concentrate on learning the clinical visit embedding and exploring the relations between visits. Although those wor... | main | Applications | 10.1609/aaai.v34i01.5428 | 34 | 01 | 833-840 | official | 1911.12216 | title_snapshot |
10.1609/aaai.v34i01.5430 | Gait Recognition for Co-Existing Multiple People Using Millimeter Wave Sensing | https://ojs.aaai.org/index.php/AAAI/article/view/5430 | https://ojs.aaai.org/index.php/AAAI/article/download/5430/5286 | [
"Zhen Meng",
"Song Fu",
"Jie Yan",
"Hongyuan Liang",
"Anfu Zhou",
"Shilin Zhu",
"Huadong Ma",
"Jianhua Liu",
"Ning Yang"
] | Gait recognition, i.e., recognizing persons from their walking postures, has found versatile applications in security check, health monitoring, and novel human-computer interaction. The millimeter-wave (mmWave) based gait recognition represents the most recent advance. Compared with traditional camera-based solutions, ... | main | Applications | 10.1609/aaai.v34i01.5430 | 34 | 01 | 849-856 | official | null | null |
10.1609/aaai.v34i01.5431 | Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning | https://ojs.aaai.org/index.php/AAAI/article/view/5431 | https://ojs.aaai.org/index.php/AAAI/article/download/5431/5287 | [
"Xiang Ni",
"Jing Li",
"Mo Yu",
"Wang Zhou",
"Kun-Lung Wu"
] | This paper considers the problem of resource allocation in stream processing, where continuous data flows must be processed in real time in a large distributed system. To maximize system throughput, the resource allocation strategy that partitions the computation tasks of a stream processing graph onto computing device... | main | Applications | 10.1609/aaai.v34i01.5431 | 34 | 01 | 857-864 | official | 1911.08517 | title_snapshot |
10.1609/aaai.v34i01.5432 | ActiveThief: Model Extraction Using Active Learning and Unannotated Public Data | https://ojs.aaai.org/index.php/AAAI/article/view/5432 | https://ojs.aaai.org/index.php/AAAI/article/download/5432/5288 | [
"Soham Pal",
"Yash Gupta",
"Aditya Shukla",
"Aditya Kanade",
"Shirish Shevade",
"Vinod Ganapathy"
] | Machine learning models are increasingly being deployed in practice. Machine Learning as a Service (MLaaS) providers expose such models to queries by third-party developers through application programming interfaces (APIs). Prior work has developed model extraction attacks, in which an attacker extracts an approximatio... | main | Applications | 10.1609/aaai.v34i01.5432 | 34 | 01 | 865-872 | official | null | null |
10.1609/aaai.v34i01.5433 | Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-Like Molecules | https://ojs.aaai.org/index.php/AAAI/article/view/5433 | https://ojs.aaai.org/index.php/AAAI/article/download/5433/5289 | [
"Yashaswi Pathak",
"Siddhartha Laghuvarapu",
"Sarvesh Mehta",
"U. Deva Priyakumar"
] | Solubility of drug molecules is related to pharmacokinetic properties such as absorption and distribution, which affects the amount of drug that is available in the body for its action. Computational or experimental evaluation of solvation free energies of drug-like molecules/solute that quantify solubilities is an ard... | main | Applications | 10.1609/aaai.v34i01.5433 | 34 | 01 | 873-880 | official | null | null |
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