paper_id string | title string | paper_url string | pdf_url string | authors list | abstract large_string | track string | primary_area string | doi string | volume string | issue string | pages string | abstract_source string | arxiv_id string | arxiv_id_source string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
10.1609/aaai.v35i1.16158 | Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification | https://ojs.aaai.org/index.php/AAAI/article/view/16158 | https://ojs.aaai.org/index.php/AAAI/article/download/16158/15965 | [
"Yi Zhou",
"Lei Huang",
"Tianfei Zhou",
"Ling Shao"
] | Chest X-rays are an important and accessible clinical imaging tool for the detection of many thoracic diseases. Over the past decade, deep learning, with a focus on the convolutional neural network (CNN), has become the most powerful computer-aided diagnosis technology for improving disease identification performance. ... | main | Application Domains | 10.1609/aaai.v35i1.16158 | 35 | 1 | 768-776 | official | 2102.13269 | title_snapshot |
10.1609/aaai.v35i1.16143 | Alternative Baselines for Low-Shot 3D Medical Image Segmentation---An Atlas Perspective | https://ojs.aaai.org/index.php/AAAI/article/view/16143 | https://ojs.aaai.org/index.php/AAAI/article/download/16143/15950 | [
"Shuxin Wang",
"Shilei Cao",
"Dong Wei",
"Cong Xie",
"Kai Ma",
"Liansheng Wang",
"Deyu Meng",
"Yefeng Zheng"
] | Low-shot (one/few-shot) segmentation has attracted increasing attention as it works well with limited annotation. State-of-the-art low-shot segmentation methods on natural images usually focus on implicit representation learning for each novel class, such as learning prototypes, deriving guidance features via masked av... | main | Application Domains | 10.1609/aaai.v35i1.16143 | 35 | 1 | 634-642 | official | null | null |
10.1609/aaai.v35i1.16144 | DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding | https://ojs.aaai.org/index.php/AAAI/article/view/16144 | https://ojs.aaai.org/index.php/AAAI/article/download/16144/15951 | [
"Zhicheng Wang",
"Biwei Huang",
"Shikui Tu",
"Kun Zhang",
"Lei Xu"
] | Most existing reinforcement learning (RL)-based portfolio management models do not take into account the market conditions, which limits their performance in risk-return balancing. In this paper, we propose DeepTrader, a deep RL method to optimize the investment policy. In particular, to tackle the risk-return balancin... | main | Application Domains | 10.1609/aaai.v35i1.16144 | 35 | 1 | 643-650 | official | null | null |
10.1609/aaai.v35i1.16145 | Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series | https://ojs.aaai.org/index.php/AAAI/article/view/16145 | https://ojs.aaai.org/index.php/AAAI/article/download/16145/15952 | [
"Yinjun Wu",
"Jingchao Ni",
"Wei Cheng",
"Bo Zong",
"Dongjin Song",
"Zhengzhang Chen",
"Yanchi Liu",
"Xuchao Zhang",
"Haifeng Chen",
"Susan B Davidson"
] | Forecasting on sparse multivariate time series (MTS) aims to model the predictors of future values of time series given their incomplete past, which is important for many emerging applications. However, most existing methods process MTS’s individually, and do not leverage the dynamic distributions underlying the MTS’s,... | main | Application Domains | 10.1609/aaai.v35i1.16145 | 35 | 1 | 651-659 | official | 2103.02164 | title_snapshot |
10.1609/aaai.v35i1.16146 | Automated Symbolic Law Discovery: A Computer Vision Approach | https://ojs.aaai.org/index.php/AAAI/article/view/16146 | https://ojs.aaai.org/index.php/AAAI/article/download/16146/15953 | [
"Hengrui Xing",
"Ansaf Salleb-Aouissi",
"Nakul Verma"
] | One of the most exciting applications of modern artificial intelligence is to automatically discover scientific laws from experimental data. This is not a trivial problem as it involves searching for a complex mathematical relationship over a large set of explanatory variables and operators that can be combined in an i... | main | Application Domains | 10.1609/aaai.v35i1.16146 | 35 | 1 | 660-668 | official | null | null |
10.1609/aaai.v35i1.16147 | Hierarchically and Cooperatively Learning Traffic Signal Control | https://ojs.aaai.org/index.php/AAAI/article/view/16147 | https://ojs.aaai.org/index.php/AAAI/article/download/16147/15954 | [
"Bingyu Xu",
"Yaowei Wang",
"Zhaozhi Wang",
"Huizhu Jia",
"Zongqing Lu"
] | Deep reinforcement learning (RL) has been applied to traffic signal control recently and demonstrated superior performance to conventional control methods. However, there are still several challenges we have to address before fully applying deep RL to traffic signal control. Firstly, the objective of traffic signal con... | main | Application Domains | 10.1609/aaai.v35i1.16147 | 35 | 1 | 669-677 | official | null | null |
10.1609/aaai.v35i1.16148 | Deep Partial Rank Aggregation for Personalized Attributes | https://ojs.aaai.org/index.php/AAAI/article/view/16148 | https://ojs.aaai.org/index.php/AAAI/article/download/16148/15955 | [
"Qianqian Xu",
"Zhiyong Yang",
"Zuyao Chen",
"Yangbangyan Jiang",
"Xiaochun Cao",
"Yuan Yao",
"Qingming Huang"
] | In this paper, we study the problem of how to aggregate pairwise personalized attributes (PA) annotations (e.g., Shoes A is more comfortable than B) from different annotators on the crowdsourcing platforms, which is an emerging topic gaining increasing attention in recent years. Given the crowdsourced annotations, the ... | main | Application Domains | 10.1609/aaai.v35i1.16148 | 35 | 1 | 678-688 | official | null | null |
10.1609/aaai.v35i1.16149 | Towards Efficient Selection of Activity Trajectories based on Diversity and Coverage | https://ojs.aaai.org/index.php/AAAI/article/view/16149 | https://ojs.aaai.org/index.php/AAAI/article/download/16149/15956 | [
"Chengcheng Yang",
"Lisi Chen",
"Hao Wang",
"Shuo Shang"
] | With the prevalence of location based services, activity trajectories are being generated at a rapid pace. The activity trajectory data enriches traditional trajectory data with semantic activities of users, which not only shows where the users have been, but also the preference of users. However, the large volume of d... | main | Application Domains | 10.1609/aaai.v35i1.16149 | 35 | 1 | 689-696 | official | null | null |
10.1609/aaai.v35i1.16150 | Minimizing Labeling Cost for Nuclei Instance Segmentation and Classification with Cross-domain Images and Weak Labels | https://ojs.aaai.org/index.php/AAAI/article/view/16150 | https://ojs.aaai.org/index.php/AAAI/article/download/16150/15957 | [
"Siqi Yang",
"Jun Zhang",
"Junzhou Huang",
"Brian C. Lovell",
"Xiao Han"
] | Nucleus instance segmentation and classification in histopathological images is an essential prerequisite in pathology diagnosis/prognosis. However, nucleus annotations (e.g., segmentation and labeling) require domain experts, and annotating nuclei at pixel-level is time-consuming and labor-intensive. Moreover, nuclei ... | main | Application Domains | 10.1609/aaai.v35i1.16150 | 35 | 1 | 697-705 | official | null | null |
10.1609/aaai.v35i1.16152 | GRASP: Generic Framework for Health Status Representation Learning Based on Incorporating Knowledge from Similar Patients | https://ojs.aaai.org/index.php/AAAI/article/view/16152 | https://ojs.aaai.org/index.php/AAAI/article/download/16152/15959 | [
"Chaohe Zhang",
"Xin Gao",
"Liantao Ma",
"Yasha Wang",
"Jiangtao Wang",
"Wen Tang"
] | Deep learning models have been applied to many healthcare tasks based on electronic medical records (EMR) data and shown substantial performance. Existing methods commonly embed the records of a single patient into a representation for medical tasks. Such methods learn inadequate representations and lead to inferior pe... | main | Application Domains | 10.1609/aaai.v35i1.16152 | 35 | 1 | 715-723 | official | null | null |
10.1609/aaai.v35i1.16153 | Window Loss for Bone Fracture Detection and Localization in X-ray Images with Point-based Annotation | https://ojs.aaai.org/index.php/AAAI/article/view/16153 | https://ojs.aaai.org/index.php/AAAI/article/download/16153/15960 | [
"Xinyu Zhang",
"Yirui Wang",
"Chi-Tung Cheng",
"Le Lu",
"Adam P. Harrison",
"Jing Xiao",
"Chien-Hung Liao",
"Shun Miao"
] | Object detection methods are widely adopted for computer-aided diagnosis using medical images. Anomalous findings are usually treated as objects that are described by bounding boxes. Yet, many pathological findings, e.g., bone fractures, cannot be clearly defined by bounding boxes, owing to considerable instance, shape... | main | Application Domains | 10.1609/aaai.v35i1.16153 | 35 | 1 | 724-732 | official | 2012.04066 | title_judge |
10.1609/aaai.v35i1.16154 | A Spatial Regulated Patch-Wise Approach for Cervical Dysplasia Diagnosis | https://ojs.aaai.org/index.php/AAAI/article/view/16154 | https://ojs.aaai.org/index.php/AAAI/article/download/16154/15961 | [
"Ying Zhang",
"Yifang Yin",
"Zhenguang Liu",
"Roger Zimmermann"
] | Cervical dysplasia diagnosis via visual investigation is a challenging problem. Recent approaches use deep learning techniques to extract features and require the downsampling of high-resolution cervical screening images to smaller sizes for training. Such a reduction may result in the loss of visual details that appea... | main | Application Domains | 10.1609/aaai.v35i1.16154 | 35 | 1 | 733-740 | official | null | null |
10.1609/aaai.v35i1.16155 | Online 3D Bin Packing with Constrained Deep Reinforcement Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16155 | https://ojs.aaai.org/index.php/AAAI/article/download/16155/15962 | [
"Hang Zhao",
"Qijin She",
"Chenyang Zhu",
"Yin Yang",
"Kai Xu"
] | We solve a challenging yet practically useful variant of 3D Bin Packing Problem (3D-BPP). In our problem, the agent has limited information about the items to be packed into a single bin, and an item must be packed immediately after its arrival without buffering or readjusting. The item's placement also subjects to the... | main | Application Domains | 10.1609/aaai.v35i1.16155 | 35 | 1 | 741-749 | official | 2006.14978 | title_snapshot |
10.1609/aaai.v35i1.16156 | DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems | https://ojs.aaai.org/index.php/AAAI/article/view/16156 | https://ojs.aaai.org/index.php/AAAI/article/download/16156/15963 | [
"Xiangyu Zhao",
"Changsheng Gu",
"Haoshenglun Zhang",
"Xiwang Yang",
"Xiaobing Liu",
"Jiliang Tang",
"Hui Liu"
] | With the recent prevalence of Reinforcement Learning (RL), there have been tremendous interests in utilizing RL for online advertising in recommendation platforms (e.g., e-commerce and news feed sites). However, most RL-based advertising algorithms focus on optimizing ads' revenue while ignoring the possible negative i... | main | Application Domains | 10.1609/aaai.v35i1.16156 | 35 | 1 | 750-758 | official | 1909.03602 | title_snapshot |
10.1609/aaai.v35i1.16157 | Towards Balanced Defect Prediction with Better Information Propagation | https://ojs.aaai.org/index.php/AAAI/article/view/16157 | https://ojs.aaai.org/index.php/AAAI/article/download/16157/15964 | [
"Xianda Zheng",
"Yuan-Fang Li",
"Huan Gao",
"Yuncheng Hua",
"Guilin Qi"
] | Defect prediction, the task of predicting the presence of defects in source code artifacts, has broad application in software development. Defect prediction faces two major challenges, label scarcity, where only a small percentage of code artifacts are labeled, and data imbalance, where the majority of labeled artifact... | main | Application Domains | 10.1609/aaai.v35i1.16157 | 35 | 1 | 759-767 | official | null | null |
10.1609/aaai.v35i1.16151 | Bigram and Unigram Based Text Attack via Adaptive Monotonic Heuristic Search | https://ojs.aaai.org/index.php/AAAI/article/view/16151 | https://ojs.aaai.org/index.php/AAAI/article/download/16151/15958 | [
"Xinghao Yang",
"Weifeng Liu",
"James Bailey",
"Dacheng Tao",
"Wei Liu"
] | Deep neural networks (DNNs) are known to be vulnerable to adversarial images, while their robustness in text classification are rarely studied. Several lines of text attack methods have been proposed in the literature, such as character-level, word-level, and sentence-level attacks. However, it is still a challenge to ... | main | Application Domains | 10.1609/aaai.v35i1.16151 | 35 | 1 | 706-714 | official | null | null |
10.1609/aaai.v35i1.16132 | Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models | https://ojs.aaai.org/index.php/AAAI/article/view/16132 | https://ojs.aaai.org/index.php/AAAI/article/download/16132/15939 | [
"Rongye Shi",
"Zhaobin Mo",
"Xuan Di"
] | Traffic state estimation (TSE) reconstructs the traffic variables (e.g., density or average velocity) on road segments using partially observed data, which is important for traffic managements. Traditional TSE approaches mainly bifurcate into two categories: model-driven and data-driven, and each of them has shortcomin... | main | Application Domains | 10.1609/aaai.v35i1.16132 | 35 | 1 | 540-547 | official | null | null |
10.1609/aaai.v35i1.16131 | GTA: Graph Truncated Attention for Retrosynthesis | https://ojs.aaai.org/index.php/AAAI/article/view/16131 | https://ojs.aaai.org/index.php/AAAI/article/download/16131/15938 | [
"Seung-Woo Seo",
"You Young Song",
"June Yong Yang",
"Seohui Bae",
"Hankook Lee",
"Jinwoo Shin",
"Sung Ju Hwang",
"Eunho Yang"
] | Retrosynthesis is the task of predicting reactant molecules from a given product molecule and is, important in organic chemistry because the identification of a synthetic path is as demanding as the discovery of new chemical compounds. Recently, the retrosynthesis task has been solved automatically without human expert... | main | Application Domains | 10.1609/aaai.v35i1.16131 | 35 | 1 | 531-539 | official | null | null |
10.1609/aaai.v35i1.16130 | Integrating Static and Dynamic Data for Improved Prediction of Cognitive Declines Using Augmented Genotype-Phenotype Representations | https://ojs.aaai.org/index.php/AAAI/article/view/16130 | https://ojs.aaai.org/index.php/AAAI/article/download/16130/15937 | [
"Hoon Seo",
"Lodewijk Brand",
"Hua Wang",
"Feiping Nie"
] | Alzheimer’s Disease (AD) is a chronic neurodegenerative disease that causes severe problems in patients’ thinking, memory, and behavior. An early diagnosis is crucial to prevent AD progression; to this end, many algorithmic approaches have recently been proposed to predict cognitive decline. However, these predictive m... | main | Application Domains | 10.1609/aaai.v35i1.16130 | 35 | 1 | 522-530 | official | null | null |
10.1609/aaai.v35i1.16129 | StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling | https://ojs.aaai.org/index.php/AAAI/article/view/16129 | https://ojs.aaai.org/index.php/AAAI/article/download/16129/15936 | [
"Eugene Seo",
"Rebecca A. Hutchinson",
"Xiao Fu",
"Chelsea Li",
"Tyler A. Hallman",
"John Kilbride",
"W. Douglas Robinson"
] | This paper focuses on a core task in computational sustainability and statistical ecology: species distribution modeling (SDM). In SDM, the occurrence pattern of a species on a landscape is predicted by environmental features based on observations at a set of locations. At first, SDM may appear to be a binary classific... | main | Application Domains | 10.1609/aaai.v35i1.16129 | 35 | 1 | 513-521 | official | 2102.08534 | title_snapshot |
10.1609/aaai.v35i1.16128 | Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting Agent | https://ojs.aaai.org/index.php/AAAI/article/view/16128 | https://ojs.aaai.org/index.php/AAAI/article/download/16128/15935 | [
"Peter Schaldenbrand",
"Jean Oh"
] | The objective of most Reinforcement Learning painting agents is to minimize the loss between a target image and the paint canvas. Human painter artistry emphasizes important features of the target image rather than simply reproducing it. Using adversarial or L2 losses in the RL painting models, although its final outpu... | main | Application Domains | 10.1609/aaai.v35i1.16128 | 35 | 1 | 505-512 | official | 2012.10043 | title_snapshot |
10.1609/aaai.v35i1.16127 | Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach | https://ojs.aaai.org/index.php/AAAI/article/view/16127 | https://ojs.aaai.org/index.php/AAAI/article/download/16127/15934 | [
"Ramit Sawhney",
"Shivam Agarwal",
"Arnav Wadhwa",
"Tyler Derr",
"Rajiv Ratn Shah"
] | Quantitative trading and investment decision making are intricate financial tasks that rely on accurate stock selection. Despite advances in deep learning that have made significant progress in the complex and highly stochastic stock prediction problem, modern solutions face two significant limitations. They do not dir... | main | Application Domains | 10.1609/aaai.v35i1.16127 | 35 | 1 | 497-504 | official | null | null |
10.1609/aaai.v35i1.16126 | CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG | https://ojs.aaai.org/index.php/AAAI/article/view/16126 | https://ojs.aaai.org/index.php/AAAI/article/download/16126/15933 | [
"Pritam Sarkar",
"Ali Etemad"
] | Electrocardiogram (ECG) is the electrical measurement of cardiac activity, whereas Photoplethysmogram (PPG) is the optical measurement of volumetric changes in blood circulation. While both signals are used for heart rate monitoring, from a medical perspective, ECG is more useful as it carries additional cardiac inform... | main | Application Domains | 10.1609/aaai.v35i1.16126 | 35 | 1 | 488-496 | official | 2010.00104 | title_snapshot |
10.1609/aaai.v35i1.16125 | DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis | https://ojs.aaai.org/index.php/AAAI/article/view/16125 | https://ojs.aaai.org/index.php/AAAI/article/download/16125/15932 | [
"Md Mahmudur Rahman",
"Koji Matsuo",
"Shinya Matsuzaki",
"Sanjay Purushotham"
] | Competing Risk Analysis (CRA) aims at the correct estimation of the marginal probability of occurrence of an event in the presence of competing events. Many of the statistical approaches developed for CRA are limited by strong assumptions about the underlying stochastic processes. To overcome these issues and to handle... | main | Application Domains | 10.1609/aaai.v35i1.16125 | 35 | 1 | 479-487 | official | null | null |
10.1609/aaai.v35i1.16124 | Research Reproducibility as a Survival Analysis | https://ojs.aaai.org/index.php/AAAI/article/view/16124 | https://ojs.aaai.org/index.php/AAAI/article/download/16124/15931 | [
"Edward Raff"
] | There has been increasing concern within the machine learning community that we are in a reproducibility crisis. As many have begun to work on this problem, all work we are aware of treat the issue of reproducibility as an intrinsic binary property: a paper is or is not reproducible. Instead, we consider modeling the r... | main | Application Domains | 10.1609/aaai.v35i1.16124 | 35 | 1 | 469-478 | official | 2012.09932 | title_snapshot |
10.1609/aaai.v35i1.16123 | Queue-Learning: A Reinforcement Learning Approach for Providing Quality of Service | https://ojs.aaai.org/index.php/AAAI/article/view/16123 | https://ojs.aaai.org/index.php/AAAI/article/download/16123/15930 | [
"Majid Raeis",
"Ali Tizghadam",
"Alberto Leon-Garcia"
] | End-to-end delay is a critical attribute of quality of service (QoS) in application domains such as cloud computing and computer networks. This metric is particularly important in tandem service systems, where the end-to-end service is provided through a chain of services. Service-rate control is a common mechanism for... | main | Application Domains | 10.1609/aaai.v35i1.16123 | 35 | 1 | 461-468 | official | 2101.04627 | title_snapshot |
10.1609/aaai.v35i1.16137 | Fully Exploiting Cascade Graphs for Real-time Forwarding Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/16137 | https://ojs.aaai.org/index.php/AAAI/article/download/16137/15944 | [
"Xiangyun Tang",
"Dongliang Liao",
"Weijie Huang",
"Jin Xu",
"Liehuang Zhu",
"Meng Shen"
] | Real-time forwarding prediction for predicting online contents' popularity is beneficial to various social applications for enhancing interactive social behaviors. Cascade graphs, formed by online contents' propagation, play a vital role in real-time forwarding prediction. Existing cascade graph modeling methods are in... | main | Application Domains | 10.1609/aaai.v35i1.16137 | 35 | 1 | 582-590 | official | null | null |
10.1609/aaai.v35i1.16134 | Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multi-modal Data | https://ojs.aaai.org/index.php/AAAI/article/view/16134 | https://ojs.aaai.org/index.php/AAAI/article/download/16134/15941 | [
"Amila Silva",
"Ling Luo",
"Shanika Karunasekera",
"Christopher Leckie"
] | With the rapid evolution of social media, fake news has become a significant social problem, which cannot be addressed in a timely manner using manual investigation. This has motivated numerous studies on automating fake news detection. Most studies explore supervised training models with different modalities (e.g., te... | main | Application Domains | 10.1609/aaai.v35i1.16134 | 35 | 1 | 557-565 | official | 2102.06314 | title_snapshot |
10.1609/aaai.v35i1.16142 | Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management | https://ojs.aaai.org/index.php/AAAI/article/view/16142 | https://ojs.aaai.org/index.php/AAAI/article/download/16142/15949 | [
"Rundong Wang",
"Hongxin Wei",
"Bo An",
"Zhouyan Feng",
"Jun Yao"
] | Portfolio management via reinforcement learning is at the forefront of fintech research, which explores how to optimally reallocate a fund into different financial assets over the long term by trial-and-error. Existing methods are impractical since they usually assume each reallocation can be finished immediately and t... | main | Application Domains | 10.1609/aaai.v35i1.16142 | 35 | 1 | 626-633 | official | null | null |
10.1609/aaai.v35i1.16141 | PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16141 | https://ojs.aaai.org/index.php/AAAI/article/download/16141/15948 | [
"Qin Wang",
"Boyuan Wang",
"Zhenlei Xu",
"Jiaxiang Wu",
"Peilin Zhao",
"Zhen Li",
"Sheng Wang",
"Junzhou Huang",
"Shuguang Cui"
] | Protein secondary structure prediction (PSSP) is an essential task in computational biology. To achieve the accurate PSSP, the general and vital feature engineering is to use multiple sequence alignment (MSA) for Position-Specific Scoring Matrix (PSSM) extraction. However, when only low-quality PSSM can be obtained due... | main | Application Domains | 10.1609/aaai.v35i1.16141 | 35 | 1 | 617-625 | official | null | null |
10.1609/aaai.v35i1.16140 | Sketch Generation with Drawing Process Guided by Vector Flow and Grayscale | https://ojs.aaai.org/index.php/AAAI/article/view/16140 | https://ojs.aaai.org/index.php/AAAI/article/download/16140/15947 | [
"Zhengyan Tong",
"Xuanhong Chen",
"Bingbing Ni",
"Xiaohang Wang"
] | We propose a novel image-to-pencil translation method that could not only generate high-quality pencil sketches but also offer the drawing process. Existing pencil sketch algorithms are based on texture rendering rather than the direct imitation of strokes, making them unable to show the drawing process but only a fina... | main | Application Domains | 10.1609/aaai.v35i1.16140 | 35 | 1 | 609-616 | official | 2012.09004 | title_snapshot |
10.1609/aaai.v35i1.16139 | DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations | https://ojs.aaai.org/index.php/AAAI/article/view/16139 | https://ojs.aaai.org/index.php/AAAI/article/download/16139/15946 | [
"Ruben Tolosana",
"Paula Delgado-Santos",
"Andres Perez-Uribe",
"Ruben Vera-Rodriguez",
"Julian Fierrez",
"Aythami Morales"
] | This study proposes DeepWriteSYN, a novel on-line handwriting synthesis approach via deep short-term representations. It comprises two modules: i) an optional and interchangeable temporal segmentation, which divides the handwriting into short-time segments consisting of individual or multiple concatenated strokes; and ... | main | Application Domains | 10.1609/aaai.v35i1.16139 | 35 | 1 | 600-608 | official | 2009.06308 | title_snapshot |
10.1609/aaai.v35i1.16138 | A Hierarchical Approach to Multi-Event Survival Analysis | https://ojs.aaai.org/index.php/AAAI/article/view/16138 | https://ojs.aaai.org/index.php/AAAI/article/download/16138/15945 | [
"Donna Tjandra",
"Yifei He",
"Jenna Wiens"
] | In multi-event survival analysis, one aims to predict the probability of multiple different events occurring over some time horizon. One typically assumes that the timing of events is drawn from some distribution conditioned on an individual's covariates. However, during training, one does not have access to this distr... | main | Application Domains | 10.1609/aaai.v35i1.16138 | 35 | 1 | 591-599 | official | null | null |
10.1609/aaai.v35i1.16136 | Traffic Shaping in E-Commercial Search Engine: Multi-Objective Online Welfare Maximization | https://ojs.aaai.org/index.php/AAAI/article/view/16136 | https://ojs.aaai.org/index.php/AAAI/article/download/16136/15943 | [
"Liucheng Sun",
"Chenwei Weng",
"Chengfu Huo",
"Weijun Ren",
"Guochuan Zhang",
"Xin Li"
] | The e-commercial search engine is the primary gateway for customers to find desired products and engage in online shopping. Besides displaying items to optimize for a single objective (i.e., relevance), ranking items needs to satisfy some other business requirements in practice. Recently, traffic shaping was introduced... | main | Application Domains | 10.1609/aaai.v35i1.16136 | 35 | 1 | 574-581 | official | null | null |
10.1609/aaai.v35i1.16135 | Oral-3D: Reconstructing the 3D Structure of Oral Cavity from Panoramic X-ray | https://ojs.aaai.org/index.php/AAAI/article/view/16135 | https://ojs.aaai.org/index.php/AAAI/article/download/16135/15942 | [
"Weinan Song",
"Yuan Liang",
"Jiawei Yang",
"Kun Wang",
"Lei He"
] | Panoramic X-ray (PX) provides a 2D picture of the patient's mouth in a panoramic view to help dentists observe the invisible disease inside the gum. However, it provides limited 2D information compared with cone-beam computed tomography (CBCT), another dental imaging method that generates a 3D picture of the oral cavit... | main | Application Domains | 10.1609/aaai.v35i1.16135 | 35 | 1 | 566-573 | official | 2003.08413 | title_judge |
10.1609/aaai.v35i1.16133 | The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network | https://ojs.aaai.org/index.php/AAAI/article/view/16133 | https://ojs.aaai.org/index.php/AAAI/article/download/16133/15940 | [
"Zijian Shi",
"Yu Chen",
"John Cartlidge"
] | In an order-driven financial market, the price of a financial asset is discovered through the interaction of orders - requests to buy or sell at a particular price - that are posted to the public limit order book (LOB). Therefore, LOB data is extremely valuable for modelling market dynamics. However, LOB data is not fr... | main | Application Domains | 10.1609/aaai.v35i1.16133 | 35 | 1 | 548-556 | official | 2103.01670 | title_snapshot |
10.1609/aaai.v35i1.16115 | Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16115 | https://ojs.aaai.org/index.php/AAAI/article/download/16115/15922 | [
"Christos Markos",
"James J. Q. Yu",
"Richard Yi Da Xu"
] | Intelligent transportation management requires not only statistical information on users' mobility patterns, but also knowledge of their corresponding transportation modes. While GPS trajectories can be readily obtained from GPS sensors found in modern smartphones and vehicles, these massive geospatial data are neither... | main | Application Domains | 10.1609/aaai.v35i1.16115 | 35 | 1 | 390-398 | official | null | null |
10.1609/aaai.v35i1.16122 | RareBERT: Transformer Architecture for Rare Disease Patient Identification using Administrative Claims | https://ojs.aaai.org/index.php/AAAI/article/view/16122 | https://ojs.aaai.org/index.php/AAAI/article/download/16122/15929 | [
"PKS Prakash",
"Srinivas Chilukuri",
"Nikhil Ranade",
"Shankar Viswanathan"
] | A rare disease is any disease that affects a very small percentage (1 in 1,500) of population. It is estimated that there are nearly 7,000 rare disease affecting 30 million patients in the U. S. alone. Most of the patients suffering from rare diseases experience multiple misdiagnoses and may never be diagnosed correctl... | main | Application Domains | 10.1609/aaai.v35i1.16122 | 35 | 1 | 453-460 | official | null | null |
10.1609/aaai.v35i1.16121 | Pragmatic Code Autocomplete | https://ojs.aaai.org/index.php/AAAI/article/view/16121 | https://ojs.aaai.org/index.php/AAAI/article/download/16121/15928 | [
"Gabriel Poesia",
"Noah Goodman"
] | Human language is ambiguous, with intended meanings recovered via pragmatic reasoning in context. Such reliance on context is essential for the efficiency of human communication. Programming languages, in stark contrast, are defined by unambiguous grammars. In this work, we aim to make programming languages more concis... | main | Application Domains | 10.1609/aaai.v35i1.16121 | 35 | 1 | 445-452 | official | null | null |
10.1609/aaai.v35i1.16120 | XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors | https://ojs.aaai.org/index.php/AAAI/article/view/16120 | https://ojs.aaai.org/index.php/AAAI/article/download/16120/15927 | [
"Cheng Peng",
"Haofu Liao",
"Gina Wong",
"Jiebo Luo",
"S. Kevin Zhou",
"Rama Chellappa"
] | A radiograph visualizes the internal anatomy of a patient through the use of X-ray, which projects 3D information onto a 2D plane. Hence, radiograph analysis naturally requires physicians to relate their prior knowledge about 3D human anatomy to 2D radiographs. Synthesizing novel radiographic views in a small range can... | main | Application Domains | 10.1609/aaai.v35i1.16120 | 35 | 1 | 436-444 | official | 2012.02407 | title_snapshot |
10.1609/aaai.v35i1.16119 | Deep Just-In-Time Inconsistency Detection Between Comments and Source Code | https://ojs.aaai.org/index.php/AAAI/article/view/16119 | https://ojs.aaai.org/index.php/AAAI/article/download/16119/15926 | [
"Sheena Panthaplackel",
"Junyi Jessy Li",
"Milos Gligoric",
"Raymond J. Mooney"
] | Natural language comments convey key aspects of source code such as implementation, usage, and pre- and post-conditions. Failure to update comments accordingly when the corresponding code is modified introduces inconsistencies, which is known to lead to confusion and software bugs. In this paper, we aim to detect wheth... | main | Application Domains | 10.1609/aaai.v35i1.16119 | 35 | 1 | 427-435 | official | 2010.01625 | title_snapshot |
10.1609/aaai.v35i1.16118 | Bringing UMAP Closer to the Speed of Light with GPU Acceleration | https://ojs.aaai.org/index.php/AAAI/article/view/16118 | https://ojs.aaai.org/index.php/AAAI/article/download/16118/15925 | [
"Corey J. Nolet",
"Victor Lafargue",
"Edward Raff",
"Thejaswi Nanditale",
"Tim Oates",
"John Zedlewski",
"Joshua Patterson"
] | The Uniform Manifold Approximation and Projection (UMAP) algorithm has become widely popular for its ease of use, quality of results, and support for exploratory, unsupervised, supervised, and semi-supervised learning. While many algorithms can be ported to a GPU in a simple and direct fashion, such efforts have result... | main | Application Domains | 10.1609/aaai.v35i1.16118 | 35 | 1 | 418-426 | official | 2008.00325 | title_snapshot |
10.1609/aaai.v35i1.16117 | Symbolic Music Generation with Transformer-GANs | https://ojs.aaai.org/index.php/AAAI/article/view/16117 | https://ojs.aaai.org/index.php/AAAI/article/download/16117/15924 | [
"Aashiq Muhamed",
"Liang Li",
"Xingjian Shi",
"Suri Yaddanapudi",
"Wayne Chi",
"Dylan Jackson",
"Rahul Suresh",
"Zachary C. Lipton",
"Alex J. Smola"
] | Autoregressive models using Transformers have emerged as the dominant approach for music generation with the goal of synthesizing minute-long compositions that exhibit large-scale musical structure. These models are commonly trained by minimizing the negative log-likelihood (NLL) of the observed sequence in an autoregr... | main | Application Domains | 10.1609/aaai.v35i1.16117 | 35 | 1 | 408-417 | official | null | null |
10.1609/aaai.v35i1.16116 | Low-Rank Registration Based Manifolds for Convection-Dominated PDEs | https://ojs.aaai.org/index.php/AAAI/article/view/16116 | https://ojs.aaai.org/index.php/AAAI/article/download/16116/15923 | [
"Rambod Mojgani",
"Maciej Balajewicz"
] | We develop an auto-encoder-type nonlinear dimensionality reduction algorithm to enable the construction of reduced order models of systems governed by convection-dominated nonlinear partial differential equations (PDEs), i.e. snapshots of solutions with large Kolmogorov n-width. Although several existing nonlinear mani... | main | Application Domains | 10.1609/aaai.v35i1.16116 | 35 | 1 | 399-407 | official | 2006.15655 | title_judge |
10.1609/aaai.v35i1.16114 | Programmatic Strategies for Real-Time Strategy Games | https://ojs.aaai.org/index.php/AAAI/article/view/16114 | https://ojs.aaai.org/index.php/AAAI/article/download/16114/15921 | [
"Julian R. H. Mariño",
"Rubens O. Moraes",
"Tassiana C. Oliveira",
"Claudio Toledo",
"Levi H. S. Lelis"
] | Search-based systems have shown to be effective for planning in zero-sum games. However, search-based approaches have important disadvantages. First, the decisions of search algorithms are mostly non-interpretable, which is problematic in domains where predictability and trust are desired such as commercial games. Seco... | main | Application Domains | 10.1609/aaai.v35i1.16114 | 35 | 1 | 381-389 | official | null | null |
10.1609/aaai.v35i1.16103 | Two-Stream Convolution Augmented Transformer for Human Activity Recognition | https://ojs.aaai.org/index.php/AAAI/article/view/16103 | https://ojs.aaai.org/index.php/AAAI/article/download/16103/15910 | [
"Bing Li",
"Wei Cui",
"Wei Wang",
"Le Zhang",
"Zhenghua Chen",
"Min Wu"
] | Recognition of human activities is an important task due to its far-reaching applications such as healthcare system, context-aware applications, and security monitoring. Recently, WiFi based human activity recognition (HAR) is becoming ubiquitous due to its non-invasiveness. Existing WiFi-based HAR methods regard WiFi ... | main | Application Domains | 10.1609/aaai.v35i1.16103 | 35 | 1 | 286-293 | official | null | null |
10.1609/aaai.v35i1.16104 | Traffic Flow Prediction with Vehicle Trajectories | https://ojs.aaai.org/index.php/AAAI/article/view/16104 | https://ojs.aaai.org/index.php/AAAI/article/download/16104/15911 | [
"Mingqian Li",
"Panrong Tong",
"Mo Li",
"Zhongming Jin",
"Jianqiang Huang",
"Xian-Sheng Hua"
] | This paper proposes a spatiotemporal deep learning framework, Trajectory-based Graph Neural Network (TrGNN), that mines the underlying causality of flows from historical vehicle trajectories and incorporates that into road traffic prediction. The vehicle trajectory transition patterns are studied to explicitly model th... | main | Application Domains | 10.1609/aaai.v35i1.16104 | 35 | 1 | 294-302 | official | null | null |
10.1609/aaai.v35i1.16105 | RevMan: Revenue-aware Multi-task Online Insurance Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/16105 | https://ojs.aaai.org/index.php/AAAI/article/download/16105/15912 | [
"Yu Li",
"Yi Zhang",
"Lu Gan",
"Gengwei Hong",
"Zimu Zhou",
"Qiang Li"
] | Online insurance is a new type of e-commerce with exponential growth. An effective recommendation model that maximizes the total revenue of insurance products listed in multiple customized sales scenarios is crucial for the success of online insurance business. Prior recommendation models are ineffective because they f... | main | Application Domains | 10.1609/aaai.v35i1.16105 | 35 | 1 | 303-310 | official | null | null |
10.1609/aaai.v35i1.16106 | MeInGame: Create a Game Character Face from a Single Portrait | https://ojs.aaai.org/index.php/AAAI/article/view/16106 | https://ojs.aaai.org/index.php/AAAI/article/download/16106/15913 | [
"Jiangke Lin",
"Yi Yuan",
"Zhengxia Zou"
] | Many deep learning based 3D face reconstruction methods have been proposed recently, however, few of them have applications in games. Current game character customization systems either require players to manually adjust considerable face attributes to obtain the desired face, or have limited freedom of facial shape an... | main | Application Domains | 10.1609/aaai.v35i1.16106 | 35 | 1 | 311-319 | official | 2102.02371 | title_snapshot |
10.1609/aaai.v35i1.16107 | Community-Aware Multi-Task Transportation Demand Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/16107 | https://ojs.aaai.org/index.php/AAAI/article/download/16107/15914 | [
"Hao Liu",
"Qiyu Wu",
"Fuzhen Zhuang",
"Xinjiang Lu",
"Dejing Dou",
"Hui Xiong"
] | Transportation demand prediction is of great importance to urban governance and has become an essential function in many online applications. While many efforts have been made for regional transportation demand prediction, predicting the diversified transportation demand for different communities (e.g., the aged, the j... | main | Application Domains | 10.1609/aaai.v35i1.16107 | 35 | 1 | 320-327 | official | null | null |
10.1609/aaai.v35i1.16108 | Asynchronous Stochastic Gradient Descent for Extreme-Scale Recommender Systems | https://ojs.aaai.org/index.php/AAAI/article/view/16108 | https://ojs.aaai.org/index.php/AAAI/article/download/16108/15915 | [
"Lewis Liu",
"Kun Zhao"
] | Recommender systems are influential for many internet applications. As the size of the dataset provided for a recommendation model grows rapidly, how to utilize such amount of data effectively matters a lot. For a typical Click-Through-Rate(CTR) prediction model, the amount of daily samples can probably be up to hundre... | main | Application Domains | 10.1609/aaai.v35i1.16108 | 35 | 1 | 328-335 | official | null | null |
10.1609/aaai.v35i1.16109 | In-game Residential Home Planning via Visual Context-aware Global Relation Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16109 | https://ojs.aaai.org/index.php/AAAI/article/download/16109/15916 | [
"Lijuan Liu",
"Yin Yang",
"Yi Yuan",
"Tianjia Shao",
"He Wang",
"Kun Zhou"
] | In this paper, we propose an effective global relation learning algorithm to recommend an appropriate location of a building unit for in-game customization of residential home complex. Given a construction layout, we propose a visual context-aware graph generation network that learns the implicit global relations among... | main | Application Domains | 10.1609/aaai.v35i1.16109 | 35 | 1 | 336-343 | official | 2102.04035 | title_snapshot |
10.1609/aaai.v35i1.16110 | Relational Classification of Biological Cells in Microscopy Images | https://ojs.aaai.org/index.php/AAAI/article/view/16110 | https://ojs.aaai.org/index.php/AAAI/article/download/16110/15917 | [
"Ping Liu",
"Mustafa Bilgic"
] | We investigate the relational classification of biological cells in 2D microscopy images. Rather than treating each cell image independently, we investigate whether and how the neighborhood information of a cell can be informative for its prediction. We propose a Relational Long Short-Term Memory (R-LSTM) algorithm, co... | main | Application Domains | 10.1609/aaai.v35i1.16110 | 35 | 1 | 344-352 | official | null | null |
10.1609/aaai.v35i1.16111 | Deep Style Transfer for Line Drawings | https://ojs.aaai.org/index.php/AAAI/article/view/16111 | https://ojs.aaai.org/index.php/AAAI/article/download/16111/15918 | [
"Xueting Liu",
"Wenliang Wu",
"Huisi Wu",
"Zhenkun Wen"
] | Line drawings are frequently used to illustrate ideas and concepts in digital documents and presentations. To compose a line drawing, it is common for users to retrieve multiple line drawings from the Internet and combine them as one image. However, different line drawings may have different line styles and are visuall... | main | Application Domains | 10.1609/aaai.v35i1.16111 | 35 | 1 | 353-361 | official | null | null |
10.1609/aaai.v35i1.16112 | RNA Secondary Structure Representation Network for RNA-proteins Binding Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/16112 | https://ojs.aaai.org/index.php/AAAI/article/download/16112/15919 | [
"Ziyi Liu",
"Fulin Luo",
"Bo Du"
] | RNA-binding proteins (RBPs) play a significant part in several biological processes in the living cell, such as gene regulation and mRNA localization. Several deep learning methods, especially the model based on convolutional neural network(CNN), have been used to predict the binding sites. However, previous methods fa... | main | Application Domains | 10.1609/aaai.v35i1.16112 | 35 | 1 | 362-370 | official | null | null |
10.1609/aaai.v35i1.16113 | PANTHER: Pathway Augmented Nonnegative Tensor Factorization for HighER-order Feature Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16113 | https://ojs.aaai.org/index.php/AAAI/article/download/16113/15920 | [
"Yuan Luo",
"Chengsheng Mao"
] | Genetic pathways usually encode molecular mechanisms that can inform targeted interventions. It is often challenging for existing machine learning approaches to jointly model genetic pathways (higher-order features) and variants (atomic features), and present to clinicians interpretable models. In order to build more a... | main | Application Domains | 10.1609/aaai.v35i1.16113 | 35 | 1 | 371-380 | official | 2012.08580 | title_snapshot |
10.1609/aaai.v35i1.16093 | SDGNN: Learning Node Representation for Signed Directed Networks | https://ojs.aaai.org/index.php/AAAI/article/view/16093 | https://ojs.aaai.org/index.php/AAAI/article/download/16093/15900 | [
"Junjie Huang",
"Huawei Shen",
"Liang Hou",
"Xueqi Cheng"
] | Network embedding is aimed at mapping nodes in a network into low-dimensional vector representations. Graph Neural Networks (GNNs) have received widespread attention and lead to state-of-the-art performance in learning node representations. However, most GNNs only work in unsigned networks, where only positive links ex... | main | Application Domains | 10.1609/aaai.v35i1.16093 | 35 | 1 | 196-203 | official | 2101.02390 | title_snapshot |
10.1609/aaai.v35i1.16083 | Universal Trading for Order Execution with Oracle Policy Distillation | https://ojs.aaai.org/index.php/AAAI/article/view/16083 | https://ojs.aaai.org/index.php/AAAI/article/download/16083/15890 | [
"Yuchen Fang",
"Kan Ren",
"Weiqing Liu",
"Dong Zhou",
"Weinan Zhang",
"Jiang Bian",
"Yong Yu",
"Tie-Yan Liu"
] | As a fundamental problem in algorithmic trading, order execution aims at fulfilling a specific trading order, either liquidation or acquirement, for a given instrument. Towards effective execution strategy, recent years have witnessed the shift from the analytical view with model-based market assumptions to model-free ... | main | Application Domains | 10.1609/aaai.v35i1.16083 | 35 | 1 | 107-115 | official | 2103.10860 | title_snapshot |
10.1609/aaai.v35i1.16084 | Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction | https://ojs.aaai.org/index.php/AAAI/article/view/16084 | https://ojs.aaai.org/index.php/AAAI/article/download/16084/15891 | [
"Chun-Mei Feng",
"Zhanyuan Yang",
"Geng Chen",
"Yong Xu",
"Ling Shao"
] | Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration by obtaining multiple undersampled images simultaneously through parallel imaging has always been the subject of research. In this paper, we propose the Dual-Octave Convolution (Dual-OctConv), which is capable of learning m... | main | Application Domains | 10.1609/aaai.v35i1.16084 | 35 | 1 | 116-124 | official | 2104.05345 | title_snapshot |
10.1609/aaai.v35i1.16085 | MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization | https://ojs.aaai.org/index.php/AAAI/article/view/16085 | https://ojs.aaai.org/index.php/AAAI/article/download/16085/15892 | [
"Tianfan Fu",
"Cao Xiao",
"Xinhao Li",
"Lucas M. Glass",
"Jimeng Sun"
] | Molecule optimization is a fundamental task for accelerating drug discovery, with the goal of generating new valid molecules that maximize multiple drug properties while maintaining similarity to the input molecule. Existing generative models and reinforcement learning approaches made initial success, but still face di... | main | Application Domains | 10.1609/aaai.v35i1.16085 | 35 | 1 | 125-133 | official | 2010.02318 | title_snapshot |
10.1609/aaai.v35i1.16086 | ECG ODE-GAN: Learning Ordinary Differential Equations of ECG Dynamics via Generative Adversarial Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16086 | https://ojs.aaai.org/index.php/AAAI/article/download/16086/15893 | [
"Tomer Golany",
"Daniel Freedman",
"Kira Radinsky"
] | Understanding the dynamics of complex biological and physiological systems has been explored for many years in the form of physically-based mathematical simulators. The behavior of a physical system is often described via ordinary differential equations (ODE), referred to as the dynamics. In the standard case, the dyna... | main | Application Domains | 10.1609/aaai.v35i1.16086 | 35 | 1 | 134-141 | official | null | null |
10.1609/aaai.v35i1.16087 | Towered Actor Critic For Handling Multiple Action Types In Reinforcement Learning For Drug Discovery | https://ojs.aaai.org/index.php/AAAI/article/view/16087 | https://ojs.aaai.org/index.php/AAAI/article/download/16087/15894 | [
"Sai Krishna Gottipati",
"Yashaswi Pathak",
"Boris Sattarov",
"Sahir",
"Rohan Nuttall",
"Mohammad Amini",
"Matthew E. Taylor",
"Sarath Chandar"
] | Reinforcement learning (RL) has made significant progress in both abstract and real-world domains, but the majority of state-of-the-art algorithms deal only with monotonic actions. However, some applications require agents to reason over different types of actions. Our application simulates reaction-based molecule gene... | main | Application Domains | 10.1609/aaai.v35i1.16087 | 35 | 1 | 142-150 | official | null | null |
10.1609/aaai.v35i1.16088 | Hierarchical Graph Convolution Network for Traffic Forecasting | https://ojs.aaai.org/index.php/AAAI/article/view/16088 | https://ojs.aaai.org/index.php/AAAI/article/download/16088/15895 | [
"Kan Guo",
"Yongli Hu",
"Yanfeng Sun",
"Sean Qian",
"Junbin Gao",
"Baocai Yin"
] | Traffic forecasting is attracting considerable interest due to its widespread application in intelligent transportation systems. Given the complex and dynamic traffic data, many methods focus on how to establish a spatial-temporal model to express the non-stationary traffic patterns. Recently, the latest Graph Convolut... | main | Application Domains | 10.1609/aaai.v35i1.16088 | 35 | 1 | 151-159 | official | null | null |
10.1609/aaai.v35i1.16089 | Automated Lay Language Summarization of Biomedical Scientific Reviews | https://ojs.aaai.org/index.php/AAAI/article/view/16089 | https://ojs.aaai.org/index.php/AAAI/article/download/16089/15896 | [
"Yue Guo",
"Wei Qiu",
"Yizhong Wang",
"Trevor Cohen"
] | Health literacy has emerged as a crucial factor in making appropriate health decisions and ensuring treatment outcomes. However, medical jargon and the complex structure of professional language in this domain make health information especially hard to interpret. Thus, there is an urgent unmet need for automated method... | main | Application Domains | 10.1609/aaai.v35i1.16089 | 35 | 1 | 160-168 | official | 2012.12573 | title_snapshot |
10.1609/aaai.v35i1.16090 | Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances | https://ojs.aaai.org/index.php/AAAI/article/view/16090 | https://ojs.aaai.org/index.php/AAAI/article/download/16090/15897 | [
"Sijie He",
"Xinyan Li",
"Timothy DelSole",
"Pradeep Ravikumar",
"Arindam Banerjee"
] | Sub-seasonal forecasting (SSF) focuses on predicting key variables such as temperature and precipitation on the 2-week to 2-month time scale. Skillful SSF would have immense societal value in such areas as agricultural productivity, water resource management, and emergency planning for extreme weather events. However, ... | main | Application Domains | 10.1609/aaai.v35i1.16090 | 35 | 1 | 169-177 | official | 2006.07972 | title_snapshot |
10.1609/aaai.v35i1.16091 | Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs | https://ojs.aaai.org/index.php/AAAI/article/view/16091 | https://ojs.aaai.org/index.php/AAAI/article/download/16091/15898 | [
"Wen-Yi Hsiao",
"Jen-Yu Liu",
"Yin-Cheng Yeh",
"Yi-Hsuan Yang"
] | To apply neural sequence models such as the Transformers to music generation tasks, one has to represent a piece of music by a sequence of tokens drawn from a finite set of pre-defined vocabulary. Such a vocabulary usually involves tokens of various types. For example, to describe a musical note, one needs separate tok... | main | Application Domains | 10.1609/aaai.v35i1.16091 | 35 | 1 | 178-186 | official | 2101.02402 | title_snapshot |
10.1609/aaai.v35i1.16092 | Modeling the Compatibility of Stem Tracks to Generate Music Mashups | https://ojs.aaai.org/index.php/AAAI/article/view/16092 | https://ojs.aaai.org/index.php/AAAI/article/download/16092/15899 | [
"Jiawen Huang",
"Ju-Chiang Wang",
"Jordan B. L. Smith",
"Xuchen Song",
"Yuxuan Wang"
] | A music mashup combines audio elements from two or more songs to create a new work. To reduce the time and effort required to make them, researchers have developed algorithms that predict the compatibility of audio elements. Prior work has focused on mixing unaltered excerpts, but advances in source separation enable t... | main | Application Domains | 10.1609/aaai.v35i1.16092 | 35 | 1 | 187-195 | official | 2103.14208 | title_snapshot |
10.1609/aaai.v35i1.16094 | The Causal Learning of Retail Delinquency | https://ojs.aaai.org/index.php/AAAI/article/view/16094 | https://ojs.aaai.org/index.php/AAAI/article/download/16094/15901 | [
"Yiyan Huang",
"Cheuk Hang Leung",
"Xing Yan",
"Qi Wu",
"Nanbo Peng",
"Dongdong Wang",
"Zhixiang Huang"
] | This paper focuses on the expected difference in borrower's repayment when there is a change in the lender's credit decisions. Classical estimators overlook the confounding effects and hence the estimation error can be magnificent. As such, we propose another approach to construct the estimators such that the error can... | main | Application Domains | 10.1609/aaai.v35i1.16094 | 35 | 1 | 204-212 | official | 2012.09448 | title_snapshot |
10.1609/aaai.v35i1.16095 | Deep Portfolio Optimization via Distributional Prediction of Residual Factors | https://ojs.aaai.org/index.php/AAAI/article/view/16095 | https://ojs.aaai.org/index.php/AAAI/article/download/16095/15902 | [
"Kentaro Imajo",
"Kentaro Minami",
"Katsuya Ito",
"Kei Nakagawa"
] | Recent developments in deep learning techniques have motivated intensive research in machine learning-aided stock trading strategies. However, since the financial market has a highly non-stationary nature hindering the application of typical data-hungry machine learning methods, leveraging financial inductive biases is... | main | Application Domains | 10.1609/aaai.v35i1.16095 | 35 | 1 | 213-222 | official | 2012.07245 | title_snapshot |
10.1609/aaai.v35i1.16096 | Complex Coordinate-Based Meta-Analysis with Probabilistic Programming | https://ojs.aaai.org/index.php/AAAI/article/view/16096 | https://ojs.aaai.org/index.php/AAAI/article/download/16096/15903 | [
"Valentin Iovene",
"Gaston E Zanitti",
"Demian Wassermann"
] | With the growing number of published functional magnetic resonance imaging (fMRI) studies, meta-analysis databases and models have become an integral part of brain mapping research. Coordinate-based meta-analysis (CBMA) databases are built by extracting both coordinates of reported peak activations and term association... | main | Application Domains | 10.1609/aaai.v35i1.16096 | 35 | 1 | 223-231 | official | 2012.01303 | title_snapshot |
10.1609/aaai.v35i1.16097 | Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce | https://ojs.aaai.org/index.php/AAAI/article/view/16097 | https://ojs.aaai.org/index.php/AAAI/article/download/16097/15904 | [
"Houye Ji",
"Junxiong Zhu",
"Xiao Wang",
"Chuan Shi",
"Bai Wang",
"Xiaoye Tan",
"Yanghua Li",
"Shaojian He"
] | The prosperous development of social e-commerce has spawned diverse recommendation demands, and accompanied a new recommendation paradigm, share recommendation. Significantly different from traditional binary recommendations (e.g., item recommendation and friend recommendation), share recommendation models ternary inter... | main | Application Domains | 10.1609/aaai.v35i1.16097 | 35 | 1 | 232-239 | official | null | null |
10.1609/aaai.v35i1.16098 | Estimating Calibrated Individualized Survival Curves with Deep Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16098 | https://ojs.aaai.org/index.php/AAAI/article/download/16098/15905 | [
"Fahad Kamran",
"Jenna Wiens"
] | In survival analysis, deep learning approaches have been proposed for estimating an individual's probability of survival over some time horizon. Such approaches can capture complex non-linear relationships, without relying on restrictive assumptions regarding the relationship between an individual's characteristics and... | main | Application Domains | 10.1609/aaai.v35i1.16098 | 35 | 1 | 240-248 | official | null | null |
10.1609/aaai.v35i1.16099 | Deep Contextual Clinical Prediction with Reverse Distillation | https://ojs.aaai.org/index.php/AAAI/article/view/16099 | https://ojs.aaai.org/index.php/AAAI/article/download/16099/15906 | [
"Rohan Kodialam",
"Rebecca Boiarsky",
"Justin Lim",
"Aditya Sai",
"Neil Dixit",
"David Sontag"
] | Healthcare providers are increasingly using machine learning to predict patient outcomes to make meaningful interventions. However, despite innovations in this area, deep learning models often struggle to match performance of shallow linear models in predicting these outcomes, making it difficult to leverage such techn... | main | Application Domains | 10.1609/aaai.v35i1.16099 | 35 | 1 | 249-258 | official | 2007.05611 | title_snapshot |
10.1609/aaai.v35i1.16100 | Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search | https://ojs.aaai.org/index.php/AAAI/article/view/16100 | https://ojs.aaai.org/index.php/AAAI/article/download/16100/15907 | [
"Li-Cheng Lan",
"Ti-Rong Wu",
"I-Chen Wu",
"Cho-Jui Hsieh"
] | Monte Carlo tree search (MCTS) has achieved state-of-the-art results in many domains such as Go and Atari games when combining with deep neural networks (DNNs). When more simulations are executed, MCTS can achieve higher performance but also requires enormous amounts of CPU and GPU resources. However, not all states re... | main | Application Domains | 10.1609/aaai.v35i1.16100 | 35 | 1 | 259-267 | official | 2012.07910 | title_snapshot |
10.1609/aaai.v35i1.16101 | Predicting Livelihood Indicators from Community-Generated Street-Level Imagery | https://ojs.aaai.org/index.php/AAAI/article/view/16101 | https://ojs.aaai.org/index.php/AAAI/article/download/16101/15908 | [
"Jihyeon Lee",
"Dylan Grosz",
"Burak Uzkent",
"Sicheng Zeng",
"Marshall Burke",
"David Lobell",
"Stefano Ermon"
] | Major decisions from governments and other large organizations rely on measurements of the populace's well-being, but making such measurements at a broad scale is expensive and thus infrequent in much of the developing world. We propose an inexpensive, scalable, and interpretable approach to predict key livelihood indi... | main | Application Domains | 10.1609/aaai.v35i1.16101 | 35 | 1 | 268-276 | official | 2006.08661 | title_snapshot |
10.1609/aaai.v35i1.16102 | Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws | https://ojs.aaai.org/index.php/AAAI/article/view/16102 | https://ojs.aaai.org/index.php/AAAI/article/download/16102/15909 | [
"Kookjin Lee",
"Kevin T. Carlberg"
] | This work proposes an approach for latent-dynamics learning that exactly enforces physical conservation laws. The method comprises two steps. First, the method computes a low-dimensional embedding of the high-dimensional dynamical-system state using deep convolutional autoencoders. This defines a low-dimensional nonlin... | main | Application Domains | 10.1609/aaai.v35i1.16102 | 35 | 1 | 277-285 | official | 1909.09754 | title_snapshot |
10.1609/aaai.v35i1.16072 | Efficient Poverty Mapping from High Resolution Remote Sensing Images | https://ojs.aaai.org/index.php/AAAI/article/view/16072 | https://ojs.aaai.org/index.php/AAAI/article/download/16072/15879 | [
"Kumar Ayush",
"Burak Uzkent",
"Kumar Tanmay",
"Marshall Burke",
"David Lobell",
"Stefano Ermon"
] | The combination of high-resolution satellite imagery and machine learning have proven useful in many sustainability-related tasks, including poverty prediction, infrastructure measurement, and forest monitoring. However, the accuracy afforded by high-resolution imagery comes at a cost, as such imagery is extremely expe... | main | Application Domains | 10.1609/aaai.v35i1.16072 | 35 | 1 | 12-20 | official | null | null |
10.1609/aaai.v35i1.16071 | The Undergraduate Games Corpus: A Dataset for Machine Perception of Interactive Media | https://ojs.aaai.org/index.php/AAAI/article/view/16071 | https://ojs.aaai.org/index.php/AAAI/article/download/16071/15878 | [
"Barrett R. Anderson",
"Adam M. Smith"
] | Machine perception research primarily focuses on processing static inputs (e.g. images and texts). We are interested in machine perception of interactive media (such as games, apps, and complex web applications) where interactive audience choices have long-term implications for the audience experience. While there is a... | main | Application Domains | 10.1609/aaai.v35i1.16071 | 35 | 1 | 3-11 | official | null | null |
10.1609/aaai.v35i1.16073 | Optimal Kidney Exchange with Immunosuppressants | https://ojs.aaai.org/index.php/AAAI/article/view/16073 | https://ojs.aaai.org/index.php/AAAI/article/download/16073/15880 | [
"Haris Aziz",
"Ágnes Cseh",
"John P. Dickerson",
"Duncan C. McElfresh"
] | Algorithms for exchange of kidneys is one of the key successful applications in market design, artificial intelligence, and operations research. Potent immunosuppressant drugs suppress the body's ability to reject a transplanted organ up to the point that a transplant across blood- or tissue-type incompatibility become... | main | Application Domains | 10.1609/aaai.v35i1.16073 | 35 | 1 | 21-29 | official | 2103.02253 | title_snapshot |
10.1609/aaai.v35i1.16074 | TreeCaps: Tree-Based Capsule Networks for Source Code Processing | https://ojs.aaai.org/index.php/AAAI/article/view/16074 | https://ojs.aaai.org/index.php/AAAI/article/download/16074/15881 | [
"Nghi D. Q. Bui",
"Yijun Yu",
"Lingxiao Jiang"
] | Recently program learning techniques have been proposed to process source code based on syntactical structures (e.g., abstract syntax trees) and/or semantic information (e.g., dependency graphs). While graphs may be better than trees at capturing code semantics, constructing the graphs from code inputs through the sema... | main | Application Domains | 10.1609/aaai.v35i1.16074 | 35 | 1 | 30-38 | official | 2009.09777 | title_snapshot |
10.1609/aaai.v35i1.16075 | A Bottom-Up DAG Structure Extraction Model for Math Word Problems | https://ojs.aaai.org/index.php/AAAI/article/view/16075 | https://ojs.aaai.org/index.php/AAAI/article/download/16075/15882 | [
"Yixuan Cao",
"Feng Hong",
"Hongwei Li",
"Ping Luo"
] | Research on automatically solving mathematical word problems (MWP) has a long history. Most recent works adopt Seq2Seq approach to predict the result equations as a sequence of quantities and operators. Although result equations can be written as a sequence, it is essentially a structure. More precisely, it is a Direct... | main | Application Domains | 10.1609/aaai.v35i1.16075 | 35 | 1 | 39-46 | official | null | null |
10.1609/aaai.v35i1.16076 | Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring | https://ojs.aaai.org/index.php/AAAI/article/view/16076 | https://ojs.aaai.org/index.php/AAAI/article/download/16076/15883 | [
"Zhen Chen",
"Jun Zhang",
"Shuanlong Che",
"Junzhou Huang",
"Xiao Han",
"Yixuan Yuan"
] | The immunohistochemistry (IHC) test of biopsy tissue is crucial to develop targeted treatment and evaluate prognosis for cancer patients. The IHC staining slide is usually digitized into the whole-slide image (WSI) with gigapixels for quantitative image analysis. To perform a whole image prediction (e.g., IHC scoring, ... | main | Application Domains | 10.1609/aaai.v35i1.16076 | 35 | 1 | 47-54 | official | null | null |
10.1609/aaai.v35i1.16077 | Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks | https://ojs.aaai.org/index.php/AAAI/article/view/16077 | https://ojs.aaai.org/index.php/AAAI/article/download/16077/15884 | [
"Rui Cheng",
"Qing Li"
] | In finance, the momentum spillovers of listed firms is well acknowledged. Only few studies predicted the trend of one firm in terms of its relevant firms. A common strategy of the pilot work is to adopt graph convolution networks (GCNs) with some predefined firm relations. However, momentum spillovers are propagated vi... | main | Application Domains | 10.1609/aaai.v35i1.16077 | 35 | 1 | 55-62 | official | null | null |
10.1609/aaai.v35i1.16078 | Differentially Private Link Prediction with Protected Connections | https://ojs.aaai.org/index.php/AAAI/article/view/16078 | https://ojs.aaai.org/index.php/AAAI/article/download/16078/15885 | [
"Abir De",
"Soumen Chakrabarti"
] | Link prediction (LP) algorithms propose to each node a ranked list of nodes that are currently non-neighbors, as the most likely candidates for future linkage. Owing to increasing concerns about privacy, users (nodes) may prefer to keep some of their connections protected or private. Motivated by this observation, our ... | main | Application Domains | 10.1609/aaai.v35i1.16078 | 35 | 1 | 63-71 | official | 1908.04849 | title_snapshot |
10.1609/aaai.v35i1.16079 | Graph Neural Network to Dilute Outliers for Refactoring Monolith Application | https://ojs.aaai.org/index.php/AAAI/article/view/16079 | https://ojs.aaai.org/index.php/AAAI/article/download/16079/15886 | [
"Utkarsh Desai",
"Sambaran Bandyopadhyay",
"Srikanth Tamilselvam"
] | Microservices are becoming the defacto design choice for software architecture. It involves partitioning the software components into finer modules such that the development can happen independently. It also provides natural benefits when deployed on the cloud since resources can be allocated dynamically to necessary c... | main | Application Domains | 10.1609/aaai.v35i1.16079 | 35 | 1 | 72-80 | official | 2102.03827 | title_snapshot |
10.1609/aaai.v35i1.16080 | KAN: Knowledge-aware Attention Network for Fake News Detection | https://ojs.aaai.org/index.php/AAAI/article/view/16080 | https://ojs.aaai.org/index.php/AAAI/article/download/16080/15887 | [
"Yaqian Dun",
"Kefei Tu",
"Chen Chen",
"Chunyan Hou",
"Xiaojie Yuan"
] | The explosive growth of fake news on social media has drawn great concern both from industrial and academic communities. There has been an increasing demand for fake news detection due to its detrimental effects. Generally, news content is condensed and full of knowledge entities. However, existing methods usually focu... | main | Application Domains | 10.1609/aaai.v35i1.16080 | 35 | 1 | 81-89 | official | null | null |
10.1609/aaai.v35i1.16081 | When Hashing Met Matching: Efficient Spatio-Temporal Search for Ridesharing | https://ojs.aaai.org/index.php/AAAI/article/view/16081 | https://ojs.aaai.org/index.php/AAAI/article/download/16081/15888 | [
"Chinmoy Dutta"
] | Shared on-demand mobility holds immense potential for urban transportation. However, finding ride matches in real-time at urban scale is a very difficult combinatorial optimization problem and mostly heuristic approaches are applied. In this work, we introduce a principled approach to this combinatorial problem. Our ap... | main | Application Domains | 10.1609/aaai.v35i1.16081 | 35 | 1 | 90-98 | official | 1809.02680 | title_snapshot |
10.1609/aaai.v35i1.16082 | Gene Regulatory Network Inference using 3D Convolutional Neural Network | https://ojs.aaai.org/index.php/AAAI/article/view/16082 | https://ojs.aaai.org/index.php/AAAI/article/download/16082/15889 | [
"Yue Fan",
"Xiuli Ma"
] | Gene regulatory networks (GRNs) consist of gene regulations between transcription factors (TFs) and their target genes. Single-cell RNA sequencing (scRNA-seq) brings both opportunities and challenges to the inference of GRNs. On the one hand, scRNA-seq data reveals statistic information of gene expressions at the singl... | main | Application Domains | 10.1609/aaai.v35i1.16082 | 35 | 1 | 99-106 | official | null | null |
10.1609/aaai.v35i1.16163 | Neural Analogical Matching | https://ojs.aaai.org/index.php/AAAI/article/view/16163 | https://ojs.aaai.org/index.php/AAAI/article/download/16163/15970 | [
"Maxwell Crouse",
"Constantine Nakos",
"Ibrahim Abdelaziz",
"Ken Forbus"
] | Analogy is core to human cognition. It allows us to solve problems based on prior experience, it governs the way we conceptualize new information, and it even influences our visual perception. The importance of analogy to humans has made it an active area of research in the broader field of artificial intelligence, res... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16163 | 35 | 1 | 809-817 | official | 2004.03573 | title_snapshot |
10.1609/aaai.v35i1.16164 | Interpretable Self-Supervised Facial Micro-Expression Learning to Predict Cognitive State and Neurological Disorders | https://ojs.aaai.org/index.php/AAAI/article/view/16164 | https://ojs.aaai.org/index.php/AAAI/article/download/16164/15971 | [
"Arun Das",
"Jeffrey Mock",
"Yufei Huang",
"Edward Golob",
"Peyman Najafirad"
] | Human behavior is the confluence of output from voluntary and involuntary motor systems. The neural activities that mediate behavior, from individual cells to distributed networks, are in a state of constant flux. Artificial intelligence (AI) research over the past decade shows that behavior, in the form of facial musc... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16164 | 35 | 1 | 818-826 | official | null | null |
10.1609/aaai.v35i1.16165 | Quantum Cognitively Motivated Decision Fusion for Video Sentiment Analysis | https://ojs.aaai.org/index.php/AAAI/article/view/16165 | https://ojs.aaai.org/index.php/AAAI/article/download/16165/15972 | [
"Dimitris Gkoumas",
"Qiuchi Li",
"Shahram Dehdashti",
"Massimo Melucci",
"Yijun Yu",
"Dawei Song"
] | Video sentiment analysis as a decision-making process is inherently complex, involving the fusion of decisions from multiple modalities and the so-caused cognitive biases. Inspired by recent advances in quantum cognition, we show that the sentiment judgment from one modality could be incompatible with the judgment from... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16165 | 35 | 1 | 827-835 | official | 2101.04406 | title_snapshot |
10.1609/aaai.v35i1.16166 | Towards a Better Understanding of VR Sickness: Physical Symptom Prediction for VR Contents | https://ojs.aaai.org/index.php/AAAI/article/view/16166 | https://ojs.aaai.org/index.php/AAAI/article/download/16166/15973 | [
"Hak Gu Kim",
"Sangmin Lee",
"Seongyeop Kim",
"Heoun-taek Lim",
"Yong Man Ro"
] | We address the black-box issue of VR sickness assessment (VRSA) by evaluating the level of physical symptoms of VR sickness. For the VR contents inducing the similar VR sickness level, the physical symptoms can vary depending on the characteristics of the contents. Most of existing VRSA methods focused on assessing the... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16166 | 35 | 1 | 836-844 | official | 2104.06780 | title_snapshot |
10.1609/aaai.v35i1.16167 | PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception | https://ojs.aaai.org/index.php/AAAI/article/view/16167 | https://ojs.aaai.org/index.php/AAAI/article/download/16167/15974 | [
"Aviv Netanyahu",
"Tianmin Shu",
"Boris Katz",
"Andrei Barbu",
"Joshua B. Tenenbaum"
] | The ability to perceive and reason about social interactions in the context of physical environments is core to human social intelligence and human-machine cooperation. However, no prior dataset or benchmark has systematically evaluated physically grounded perception of complex social interactions that go beyond short ... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16167 | 35 | 1 | 845-853 | official | 2103.01933 | title_snapshot |
10.1609/aaai.v35i1.16168 | Riemannian Embedding Banks for Common Spatial Patterns with EEG-based SPD Neural Networks | https://ojs.aaai.org/index.php/AAAI/article/view/16168 | https://ojs.aaai.org/index.php/AAAI/article/download/16168/15975 | [
"Yoon-Je Suh",
"Byung Hyung Kim"
] | Modeling non-linear data as symmetric positive definite (SPD) matrices on Riemannian manifolds has attracted much attention for various classification tasks. In the context of deep learning, SPD matrix-based Riemannian networks have been shown to be a promising solution for classifying electroencephalogram (EEG) signal... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16168 | 35 | 1 | 854-862 | official | null | null |
10.1609/aaai.v35i1.16169 | Plug-and-Play Domain Adaptation for Cross-Subject EEG-based Emotion Recognition | https://ojs.aaai.org/index.php/AAAI/article/view/16169 | https://ojs.aaai.org/index.php/AAAI/article/download/16169/15976 | [
"Li-Ming Zhao",
"Xu Yan",
"Bao-Liang Lu"
] | Human emotion decoding in affective brain-computer interfaces suffers a major setback due to the inter-subject variability of electroencephalography (EEG) signals. Existing approaches usually require amassing extensive EEG data of each new subject, which is prohibitively time-consuming along with poor user experience. ... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16169 | 35 | 1 | 863-870 | official | null | null |
10.1609/aaai.v35i1.16159 | Probabilistic Programming Bots in Intuitive Physics Game Play | https://ojs.aaai.org/index.php/AAAI/article/view/16159 | https://ojs.aaai.org/index.php/AAAI/article/download/16159/15966 | [
"Fahad Alhasoun",
"Sarah Alneghiemish"
] | Recent findings suggest that humans deploy cognitive mechanism of physics simulation engines to simulate the physics of objects. We propose a framework for bots to deploy probabilistic programming tools for interacting with intuitive physics environments. The framework employs a physics simulation in a probabilistic wa... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16159 | 35 | 1 | 778-783 | official | 2104.01980 | title_snapshot |
10.1609/aaai.v35i1.16160 | Model-Agnostic Fits for Understanding Information Seeking Patterns in Humans | https://ojs.aaai.org/index.php/AAAI/article/view/16160 | https://ojs.aaai.org/index.php/AAAI/article/download/16160/15967 | [
"Soumya Chatterjee",
"Pradeep Shenoy"
] | In decision making tasks under uncertainty, humans display characteristic biases in seeking, integrating, and acting upon information relevant to the task. Here, we reexamine data from previous carefully designed experiments, collected at scale, that measured and catalogued these biases in aggregate form. We design dee... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16160 | 35 | 1 | 784-791 | official | 2012.04858 | title_snapshot |
10.1609/aaai.v35i1.16161 | Apparently Irrational Choice as Optimal Sequential Decision Making | https://ojs.aaai.org/index.php/AAAI/article/view/16161 | https://ojs.aaai.org/index.php/AAAI/article/download/16161/15968 | [
"Haiyang Chen",
"Hyung Jin Chang",
"Andrew Howes"
] | In this paper, we propose a normative approach to modeling apparently human irrational decision making (cognitive biases) that makes use of inherently rational computational mechanisms. We view preferential choice tasks as sequential decision making problems and formulate them as Partially Observable Markov Decision Pr... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16161 | 35 | 1 | 792-800 | official | null | null |
10.1609/aaai.v35i1.16162 | Visual Relation Detection using Hybrid Analogical Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16162 | https://ojs.aaai.org/index.php/AAAI/article/download/16162/15969 | [
"Kezhen Chen",
"Ken Forbus"
] | Visual Relation Detection is currently one of the most popular problems for visual understanding. Many deep-learning models are designed for relation detection on images and have achieved impressive results. However, deep-learning models have several serious problems, including poor training-efficiency and lack of unde... | main | Cognitive Modeling and Cognitive Systems | 10.1609/aaai.v35i1.16162 | 35 | 1 | 801-808 | official | null | null |
10.1609/aaai.v35i2.16263 | Training Binary Neural Network without Batch Normalization for Image Super-Resolution | https://ojs.aaai.org/index.php/AAAI/article/view/16263 | https://ojs.aaai.org/index.php/AAAI/article/download/16263/16070 | [
"Xinrui Jiang",
"Nannan Wang",
"Jingwei Xin",
"Keyu Li",
"Xi Yang",
"Xinbo Gao"
] | Recently, binary neural network (BNN) based super-resolution (SR) methods have enjoyed initial success in the SR field. However, there is a noticeable performance gap between the binarized model and the full-precision one. Furthermore, the batch normalization (BN) in binary SR networks introduces floating-point calcula... | main | Computer Vision | 10.1609/aaai.v35i2.16263 | 35 | 2 | 1700-1707 | official | null | null |
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