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.v35i5.16554 | Communicative Message Passing for Inductive Relation Reasoning | https://ojs.aaai.org/index.php/AAAI/article/view/16554 | https://ojs.aaai.org/index.php/AAAI/article/download/16554/16361 | [
"Sijie Mai",
"Shuangjia Zheng",
"Yuedong Yang",
"Haifeng Hu"
] | Relation prediction for knowledge graphs aims at predicting missing relationships between entities. Despite the importance of inductive relation prediction, most previous works are limited to a transductive setting and cannot process previously unseen entities. The recent proposed subgraph-based relation reasoning mode... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16554 | 35 | 5 | 4294-4302 | official | 2012.08911 | title_snapshot |
10.1609/aaai.v35i5.16555 | Learning Accurate and Interpretable Decision Rule Sets from Neural Networks | https://ojs.aaai.org/index.php/AAAI/article/view/16555 | https://ojs.aaai.org/index.php/AAAI/article/download/16555/16362 | [
"Litao Qiao",
"Weijia Wang",
"Bill Lin"
] | This paper proposes a new paradigm for learning a set of independent logical rules in disjunctive normal form as an interpretable model for classification. We consider the problem of learning an interpretable decision rule set as training a neural network in a specific, yet very simple two-layer architecture. Each neur... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16555 | 35 | 5 | 4303-4311 | official | 2103.02826 | title_snapshot |
10.1609/aaai.v35i5.16556 | Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16556 | https://ojs.aaai.org/index.php/AAAI/article/download/16556/16363 | [
"Huiling Qin",
"Songyu Ke",
"Xiaodu Yang",
"Haoran Xu",
"Xianyuan Zhan",
"Yu Zheng"
] | Purchase prediction is an essential task in both online and offline retail industry, especially during major shopping festivals, when strong promotion boosts consumption dramatically. It is important for merchants to forecast such surge of sales and have better preparation. This is a challenging problem, as the purchas... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16556 | 35 | 5 | 4312-4319 | official | null | null |
10.1609/aaai.v35i5.16557 | U-BERT: Pre-training User Representations for Improved Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/16557 | https://ojs.aaai.org/index.php/AAAI/article/download/16557/16364 | [
"Zhaopeng Qiu",
"Xian Wu",
"Jingyue Gao",
"Wei Fan"
] | Learning user representation is a critical task for recommendation systems as it can encode user preference for personalized services. User representation is generally learned from behavior data, such as clicking interactions and review comments. However, for less popular domains, the behavior data is insufficient to l... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16557 | 35 | 5 | 4320-4327 | official | null | null |
10.1609/aaai.v35i5.16558 | DocParser: Hierarchical Document Structure Parsing from Renderings | https://ojs.aaai.org/index.php/AAAI/article/view/16558 | https://ojs.aaai.org/index.php/AAAI/article/download/16558/16365 | [
"Johannes Rausch",
"Octavio Martinez",
"Fabian Bissig",
"Ce Zhang",
"Stefan Feuerriegel"
] | Translating renderings (e. g. PDFs, scans) into hierarchical document structures is extensively demanded in the daily routines of many real-world applications. However, a holistic, principled approach to inferring the complete hierarchical structure in documents is missing. As a remedy, we developed “DocParser”: an end... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16558 | 35 | 5 | 4328-4338 | official | 1911.01702 | title_judge |
10.1609/aaai.v35i5.16551 | Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph | https://ojs.aaai.org/index.php/AAAI/article/view/16551 | https://ojs.aaai.org/index.php/AAAI/article/download/16551/16358 | [
"Zemin Liu",
"Yuan Fang",
"Chenghao Liu",
"Steven C.H. Hoi"
] | Node classification is an important problem on graphs. While recent advances in graph neural networks achieve promising performance, they require abundant labeled nodes for training. However, in many practical scenarios, there often exist novel classes in which only one or a few labeled nodes are available as supervisi... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16551 | 35 | 5 | 4267-4275 | official | null | null |
10.1609/aaai.v35i5.16532 | Online Learning in Variable Feature Spaces under Incomplete Supervision | https://ojs.aaai.org/index.php/AAAI/article/view/16532 | https://ojs.aaai.org/index.php/AAAI/article/download/16532/16339 | [
"Yi He",
"Xu Yuan",
"Sheng Chen",
"Xindong Wu"
] | This paper explores a new online learning problem where the input sequence lives in an over-time varying feature space and the ground-truth label of any input point is given only occasionally, making online learners less restrictive and more applicable. The crux in this setting lies in how to exploit the very limited l... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16532 | 35 | 5 | 4106-4114 | official | null | null |
10.1609/aaai.v35i5.16531 | Complete Closed Time Intervals-Related Patterns Mining | https://ojs.aaai.org/index.php/AAAI/article/view/16531 | https://ojs.aaai.org/index.php/AAAI/article/download/16531/16338 | [
"Omer David Harel",
"Robert Moskovitch"
] | Using temporal abstraction, various forms of sampled multivariate temporal data can be transformed into a uniform representation of symbolic time intervals, from which Time Intervals Related Patterns (TIRPs) can be then discovered. Hence, mining TIRPs from symbolic time intervals offers a comprehensive framework for he... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16531 | 35 | 5 | 4098-4105 | official | null | null |
10.1609/aaai.v35i5.16530 | GAN Ensemble for Anomaly Detection | https://ojs.aaai.org/index.php/AAAI/article/view/16530 | https://ojs.aaai.org/index.php/AAAI/article/download/16530/16337 | [
"Xu Han",
"Xiaohui Chen",
"Li-Ping Liu"
] | When formulated as an unsupervised learning problem, anomaly detection often requires a model to learn the distribution of normal data. Previous works modify Generative Adversarial Networks (GANs) by using encoder-decoders as generators and apply them to anomaly detection tasks. Previous studies indicate that GAN ensem... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16530 | 35 | 5 | 4090-4097 | official | 2012.07988 | title_snapshot |
10.1609/aaai.v35i5.16529 | Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks | https://ojs.aaai.org/index.php/AAAI/article/view/16529 | https://ojs.aaai.org/index.php/AAAI/article/download/16529/16336 | [
"Jindong Han",
"Hao Liu",
"Hengshu Zhu",
"Hui Xiong",
"Dejing Dou"
] | Accurate and timely air quality and weather predictions are of great importance to urban governance and human livelihood. Though many efforts have been made for air quality or weather prediction, most of them simply employ one another as feature input, which ignores the inner-connection between two predictive tasks. On... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16529 | 35 | 5 | 4081-4089 | official | 2012.15037 | title_snapshot |
10.1609/aaai.v35i5.16528 | NeuralAC: Learning Cooperation and Competition Effects for Match Outcome Prediction | https://ojs.aaai.org/index.php/AAAI/article/view/16528 | https://ojs.aaai.org/index.php/AAAI/article/download/16528/16335 | [
"Yin Gu",
"Qi Liu",
"Kai Zhang",
"Zhenya Huang",
"Runze Wu",
"Jianrong Tao"
] | Match outcome prediction in group comparison setting is a challenging but important task. Existing works mainly focus on learning individual effects or mining limited interactions between teammates, which is not sufficient for capturing complex interactions between teammates as well as between opponents. Besides, the i... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16528 | 35 | 5 | 4072-4080 | official | null | null |
10.1609/aaai.v35i5.16527 | Exploiting Behavioral Consistence for Universal User Representation | https://ojs.aaai.org/index.php/AAAI/article/view/16527 | https://ojs.aaai.org/index.php/AAAI/article/download/16527/16334 | [
"Jie Gu",
"Feng Wang",
"Qinghui Sun",
"Zhiquan Ye",
"Xiaoxiao Xu",
"Jingmin Chen",
"Jun Zhang"
] | User modeling is critical for developing personalized services in industry. A common way for user modeling is to learn user representations that can be distinguished by their interests or preferences. In this work, we focus on developing universal user representation model. The obtained universal representations are ex... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16527 | 35 | 5 | 4063-4071 | official | 2012.06146 | title_snapshot |
10.1609/aaai.v35i5.16526 | Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs | https://ojs.aaai.org/index.php/AAAI/article/view/16526 | https://ojs.aaai.org/index.php/AAAI/article/download/16526/16333 | [
"Tony Gracious",
"Shubham Gupta",
"Arun Kanthali",
"Rui M. Castro",
"Ambedkar Dukkipati"
] | Although static networks have been extensively studied in machine learning, data mining, and AI communities for many decades, the study of dynamic networks has recently taken center stage due to the prominence of social media and its effects on the dynamics of social networks. In this paper, we propose a statistical mo... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16526 | 35 | 5 | 4054-4062 | official | 1911.11455 | title_snapshot |
10.1609/aaai.v35i5.16525 | Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries | https://ojs.aaai.org/index.php/AAAI/article/view/16525 | https://ojs.aaai.org/index.php/AAAI/article/download/16525/16332 | [
"Dimitris Fotakis",
"Thanasis Pittas",
"Stratis Skoulakis"
] | We consider a natural setting where network parameters are estimated from noisy and incomplete information about the network. More specifically, we investigate how we can efficiently estimate the number of small subgraphs (e.g., edges, triangles, etc.) based on full access to one or two noisy and incomplete samples of ... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16525 | 35 | 5 | 4045-4053 | official | null | null |
10.1609/aaai.v35i5.16524 | A Hybrid Bandit Framework for Diversified Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/16524 | https://ojs.aaai.org/index.php/AAAI/article/download/16524/16331 | [
"Qinxu Ding",
"Yong Liu",
"Chunyan Miao",
"Fei Cheng",
"Haihong Tang"
] | The interactive recommender systems involve users in the recommendation procedure by receiving timely user feedback to update the recommendation policy. Therefore, they are widely used in real application scenarios. Previous interactive recommendation methods primarily focus on learning users' personalized preferences ... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16524 | 35 | 5 | 4036-4044 | official | 2012.13245 | title_snapshot |
10.1609/aaai.v35i5.16523 | Graph Neural Network-Based Anomaly Detection in Multivariate Time Series | https://ojs.aaai.org/index.php/AAAI/article/view/16523 | https://ojs.aaai.org/index.php/AAAI/article/download/16523/16330 | [
"Ailin Deng",
"Bryan Hooi"
] | Given high-dimensional time series data (e.g., sensor data), how can we detect anomalous events, such as system faults and attacks? More challengingly, how can we do this in a way that captures complex inter-sensor relationships, and detects and explains anomalies which deviate from these relationships? Recently, deep ... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16523 | 35 | 5 | 4027-4035 | official | 2106.06947 | title_snapshot |
10.1609/aaai.v35i5.16537 | On Estimating Recommendation Evaluation Metrics under Sampling | https://ojs.aaai.org/index.php/AAAI/article/view/16537 | https://ojs.aaai.org/index.php/AAAI/article/download/16537/16344 | [
"Ruoming Jin",
"Dong Li",
"Benjamin Mudrak",
"Jing Gao",
"Zhi Liu"
] | Since the recent studies (KDD'20) done by Krichene and Rendle on the sampling based top-k evaluation metric for recommendation, there have been a lot of debate on the validity of using sampling for evaluating recommendation algorithms. Though their work and the recent work done by Li et. al. (KDD'20) have proposed some... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16537 | 35 | 5 | 4147-4154 | official | 2103.01474 | title_snapshot |
10.1609/aaai.v35i5.16534 | Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/16534 | https://ojs.aaai.org/index.php/AAAI/article/download/16534/16341 | [
"Chao Huang",
"Jiahui Chen",
"Lianghao Xia",
"Yong Xu",
"Peng Dai",
"Yanqing Chen",
"Liefeng Bo",
"Jiashu Zhao",
"Jimmy Xiangji Huang"
] | Session-based recommendation plays a central role in a wide spectrum of online applications, ranging from e-commerce to online advertising services. However, the majority of existing session-based recommendation techniques (e.g., attention-based recurrent network or graph neural network) are not well-designed for captu... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16534 | 35 | 5 | 4123-4130 | official | 2110.03996 | title_snapshot |
10.1609/aaai.v35i5.16542 | Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting | https://ojs.aaai.org/index.php/AAAI/article/view/16542 | https://ojs.aaai.org/index.php/AAAI/article/download/16542/16349 | [
"Mengzhang Li",
"Zhanxing Zhu"
] | Spatial-temporal data forecasting of traffic flow is a challenging task because of complicated spatial dependencies and dynamical trends of temporal pattern between different roads. Existing frameworks usually utilize given spatial adjacency graph and sophisticated mechanisms for modeling spatial and temporal correlati... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16542 | 35 | 5 | 4189-4196 | official | 2012.09641 | title_snapshot |
10.1609/aaai.v35i5.16541 | Hierarchical Negative Binomial Factorization for Recommender Systems on Implicit Feedback | https://ojs.aaai.org/index.php/AAAI/article/view/16541 | https://ojs.aaai.org/index.php/AAAI/article/download/16541/16348 | [
"Li-Yen Kuo",
"Ming-Syan Chen"
] | When exposed to an item in a recommender system, a user may consume it (known as success exposure) or neglect it (known as failure exposure). The recently proposed methods that consider both success and failure exposure merely regard failure exposure as a constant prior, thus being capable of neither modeling various u... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16541 | 35 | 5 | 4181-4188 | official | null | null |
10.1609/aaai.v35i5.16540 | Disposable Linear Bandits for Online Recommendations | https://ojs.aaai.org/index.php/AAAI/article/view/16540 | https://ojs.aaai.org/index.php/AAAI/article/download/16540/16347 | [
"Melda Korkut",
"Andrew Li"
] | We study the classic stochastic linear bandit problem under the restriction that each arm may be selected for limited number of times. This simple constraint, which we call disposability, captures a common restriction that occurs in recommendation problems from a diverse array of applications ranging from personalized ... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16540 | 35 | 5 | 4172-4180 | official | null | null |
10.1609/aaai.v35i5.16539 | PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/16539 | https://ojs.aaai.org/index.php/AAAI/article/download/16539/16346 | [
"Minseok Kim",
"Hwanjun Song",
"Doyoung Kim",
"Kijung Shin",
"Jae-Gil Lee"
] | Point-of-interest (POI) recommendation has become an important research topic in these days. The user check-in history used as the input to POI recommendation is very imbalanced and noisy because of sparse and missing check-ins. Although sample reweighting is commonly adopted for addressing this challenge with the inpu... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16539 | 35 | 5 | 4164-4171 | official | null | null |
10.1609/aaai.v35i5.16538 | Randomized Generation of Adversary-aware Fake Knowledge Graphs to Combat Intellectual Property Theft | https://ojs.aaai.org/index.php/AAAI/article/view/16538 | https://ojs.aaai.org/index.php/AAAI/article/download/16538/16345 | [
"Snow Kang",
"Cristian Molinaro",
"Andrea Pugliese",
"V. S. Subrahmanian"
] | Knowledge Graphs (KGs) can be used to store information about software design, biomedical designs, and financial information---all domains where intellectual property and/or specialized knowledge must be kept confidential. Moreover, KGs can also be used to represent the content of technical documents. In order to deter... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16538 | 35 | 5 | 4155-4163 | official | null | null |
10.1609/aaai.v35i5.16536 | LREN: Low-Rank Embedded Network for Sample-Free Hyperspectral Anomaly Detection | https://ojs.aaai.org/index.php/AAAI/article/view/16536 | https://ojs.aaai.org/index.php/AAAI/article/download/16536/16343 | [
"Kai Jiang",
"Weiying Xie",
"Jie Lei",
"Tao Jiang",
"Yunsong Li"
] | Hyperspectral anomaly detection (HAD) is a challenging task because it explores the intrinsic structure of complex high-dimensional signals without any samples at training time. Deep neural networks (DNNs) can dig out the underlying distribution of hyperspectral data but are limited by the labeling of large-scale hyper... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16536 | 35 | 5 | 4139-4146 | official | null | null |
10.1609/aaai.v35i5.16535 | Anomaly Attribution with Likelihood Compensation | https://ojs.aaai.org/index.php/AAAI/article/view/16535 | https://ojs.aaai.org/index.php/AAAI/article/download/16535/16342 | [
"Tsuyoshi Idé",
"Amit Dhurandhar",
"Jiří Navrátil",
"Moninder Singh",
"Naoki Abe"
] | This paper addresses the task of explaining anomalous predictions of a black-box regression model. When using a black-box model, such as one to predict building energy consumption from many sensor measurements, we often have a situation where some observed samples may significantly deviate from their prediction. It may... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16535 | 35 | 5 | 4131-4138 | official | 2208.10679 | title_snapshot |
10.1609/aaai.v35i5.16533 | Knowledge-aware Coupled Graph Neural Network for Social Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/16533 | https://ojs.aaai.org/index.php/AAAI/article/download/16533/16340 | [
"Chao Huang",
"Huance Xu",
"Yong Xu",
"Peng Dai",
"Lianghao Xia",
"Mengyin Lu",
"Liefeng Bo",
"Hao Xing",
"Xiaoping Lai",
"Yanfang Ye"
] | Social recommendation task aims to predict users' preferences over items with the incorporation of social connections among users, so as to alleviate the sparse issue of collaborative filtering. While many recent efforts show the effectiveness of neural network-based social recommender systems, several important challe... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16533 | 35 | 5 | 4115-4122 | official | 2110.03987 | title_snapshot |
10.1609/aaai.v35i5.16513 | Extreme k-Center Clustering | https://ojs.aaai.org/index.php/AAAI/article/view/16513 | https://ojs.aaai.org/index.php/AAAI/article/download/16513/16320 | [
"MohammadHossein Bateni",
"Hossein Esfandiari",
"Manuela Fischer",
"Vahab Mirrokni"
] | Metric clustering is a fundamental primitive in machine learning with several applications for mining massive datasets. An important example of metric clustering is the k-center problem. While this problem has been extensively studied in distributed settings, all previous algorithms use Ω(k) space per machine and Ω(n k... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16513 | 35 | 5 | 3941-3949 | official | null | null |
10.1609/aaai.v35i5.16522 | PASSLEAF: A Pool-bAsed Semi-Supervised LEArning Framework for Uncertain Knowledge Graph Embedding | https://ojs.aaai.org/index.php/AAAI/article/view/16522 | https://ojs.aaai.org/index.php/AAAI/article/download/16522/16329 | [
"Zhu-Mu Chen",
"Mi-Yen Yeh",
"Tei-Wei Kuo"
] | In this paper, we study the problem of embedding uncertain knowledge graphs, where each relation between entities is associated with a confidence score. Observing the existing embedding methods may discard the uncertainty information, only incorporate a specific type of score function, or cause many false-negative samp... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16522 | 35 | 5 | 4019-4026 | official | null | null |
10.1609/aaai.v35i5.16521 | Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems | https://ojs.aaai.org/index.php/AAAI/article/view/16521 | https://ojs.aaai.org/index.php/AAAI/article/download/16521/16328 | [
"Zhengyu Chen",
"Ziqing Xu",
"Donglin Wang"
] | Tensor decomposition is one of the most effective techniques for multi-criteria recommendations. However, it suffers from data sparsity when dealing with three-dimensional (3D) user-item-criterion ratings. To mitigate this issue, we consider effectively incorporating the side information and cross-domain knowledge in t... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16521 | 35 | 5 | 4010-4018 | official | null | null |
10.1609/aaai.v35i5.16520 | Towards Faster Deep Collaborative Filtering via Hierarchical Decision Networks | https://ojs.aaai.org/index.php/AAAI/article/view/16520 | https://ojs.aaai.org/index.php/AAAI/article/download/16520/16327 | [
"Yu Chen",
"Sinno Jialin Pan"
] | For personalized recommendations, collaborative filtering (CF) methods aim to recommend items to users based on data of historical user-item interactions. Deep learning has indicated success in improving performance of CF methods in recent works. However, to generate an item recommendation list for each user, a lot of ... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16520 | 35 | 5 | 4001-4009 | official | null | null |
10.1609/aaai.v35i5.16519 | Leveraging Table Content for Zero-shot Text-to-SQL with Meta-Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16519 | https://ojs.aaai.org/index.php/AAAI/article/download/16519/16326 | [
"Yongrui Chen",
"Xinnan Guo",
"Chaojie Wang",
"Jian Qiu",
"Guilin Qi",
"Meng Wang",
"Huiying Li"
] | Single-table text-to-SQL aims to transform a natural language question into a SQL query according to one single table. Recent work has made promising progress on this task by pre-trained language models and a multi-submodule framework. However, zero-shot table, that is, the invisible table in the training set, is curre... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16519 | 35 | 5 | 3992-4000 | official | 2109.05395 | title_snapshot |
10.1609/aaai.v35i5.16518 | A User-Adaptive Layer Selection Framework for Very Deep Sequential Recommender Models | https://ojs.aaai.org/index.php/AAAI/article/view/16518 | https://ojs.aaai.org/index.php/AAAI/article/download/16518/16325 | [
"Lei Chen",
"Fajie Yuan",
"Jiaxi Yang",
"Xiang Ao",
"Chengming Li",
"Min Yang"
] | Sequential recommender systems (SRS) have become a research hotspot in recent studies. Because of the requirement in capturing user's dynamic interests, sequential neural network based recommender models often need to be stacked with more hidden layers (e.g., up to 100 layers) compared with standard collaborative filte... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16518 | 35 | 5 | 3984-3991 | official | null | null |
10.1609/aaai.v35i5.16517 | Revisiting Consistent Hashing with Bounded Loads | https://ojs.aaai.org/index.php/AAAI/article/view/16517 | https://ojs.aaai.org/index.php/AAAI/article/download/16517/16324 | [
"John Chen",
"Benjamin Coleman",
"Anshumali Shrivastava"
] | Dynamic load balancing lies at the heart of distributed caching. Here, the goal is to assign objects (load) to servers (computing nodes) in a way that provides load balancing while at the same time dynamically adjusts to the addition or removal of servers. Load balancing is a critical topic in many areas including clou... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16517 | 35 | 5 | 3976-3983 | official | 1908.08762 | title_snapshot |
10.1609/aaai.v35i5.16516 | Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure | https://ojs.aaai.org/index.php/AAAI/article/view/16516 | https://ojs.aaai.org/index.php/AAAI/article/download/16516/16323 | [
"Jin Chen",
"Tiezheng Ge",
"Gangwei Jiang",
"Zhiqiang Zhang",
"Defu Lian",
"Kai Zheng"
] | Ad creatives are one of the prominent mediums for online e-commerce advertisements. Ad creatives with enjoyable visual appearance may increase the click-through rate (CTR) of products. Ad creatives are typically handcrafted by advertisers and then delivered to the advertising platforms for advertisement. In recent year... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16516 | 35 | 5 | 3967-3975 | official | 2103.01453 | title_snapshot |
10.1609/aaai.v35i5.16515 | Graph Heterogeneous Multi-Relational Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/16515 | https://ojs.aaai.org/index.php/AAAI/article/download/16515/16322 | [
"Chong Chen",
"Weizhi Ma",
"Min Zhang",
"Zhaowei Wang",
"Xiuqiang He",
"Chenyang Wang",
"Yiqun Liu",
"Shaoping Ma"
] | Traditional studies on recommender systems usually leverage only one type of user behaviors (the optimization target, such as purchase), despite the fact that users also generate a large number of various types of interaction data (e.g., view, click, add-to-cart, etc). Generally, these heterogeneous multi-relational da... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16515 | 35 | 5 | 3958-3966 | official | null | null |
10.1609/aaai.v35i5.16514 | Beyond Low-frequency Information in Graph Convolutional Networks | https://ojs.aaai.org/index.php/AAAI/article/view/16514 | https://ojs.aaai.org/index.php/AAAI/article/download/16514/16321 | [
"Deyu Bo",
"Xiao Wang",
"Chuan Shi",
"Huawei Shen"
] | Graph neural networks (GNNs) have been proven to be effective in various network-related tasks. Most existing GNNs usually exploit the low-frequency signals of node features, which gives rise to one fundamental question: is the low-frequency information all we need in the real world applications? In this paper, we firs... | main | Data Mining and Knowledge Management | 10.1609/aaai.v35i5.16514 | 35 | 5 | 3950-3957 | official | 2101.00797 | title_snapshot |
10.1609/aaai.v35i6.16607 | Argument Mining Driven Analysis of Peer-Reviews | https://ojs.aaai.org/index.php/AAAI/article/view/16607 | https://ojs.aaai.org/index.php/AAAI/article/download/16607/16414 | [
"Michael Fromm",
"Evgeniy Faerman",
"Max Berrendorf",
"Siddharth Bhargava",
"Ruoxia Qi",
"Yao Zhang",
"Lukas Dennert",
"Sophia Selle",
"Yang Mao",
"Thomas Seidl"
] | Peer reviewing is a central process in modern research and essential for ensuring high quality and reliability of published work. At the same time, it is a time-consuming process and increasing interest in emerging fields often results in a high review workload, especially for senior researchers in this area. How to co... | main | AI for Conference Organization and Delivery | 10.1609/aaai.v35i6.16607 | 35 | 6 | 4758-4766 | official | 2012.07743 | title_snapshot |
10.1609/aaai.v35i6.16608 | Uncovering Latent Biases in Text: Method and Application to Peer Review | https://ojs.aaai.org/index.php/AAAI/article/view/16608 | https://ojs.aaai.org/index.php/AAAI/article/download/16608/16415 | [
"Emaad Manzoor",
"Nihar B. Shah"
] | Quantifying systematic disparities in numerical quantities such as employment rates and wages between population subgroups provides compelling evidence for the existence of societal biases. However, biases in the text written for members of different subgroups (such as in recommendation letters for male and non-male ca... | main | AI for Conference Organization and Delivery | 10.1609/aaai.v35i6.16608 | 35 | 6 | 4767-4775 | official | 2010.15300 | title_snapshot |
10.1609/aaai.v35i6.16609 | A Market-Inspired Bidding Scheme for Peer Review Paper Assignment | https://ojs.aaai.org/index.php/AAAI/article/view/16609 | https://ojs.aaai.org/index.php/AAAI/article/download/16609/16416 | [
"Reshef Meir",
"Jérôme Lang",
"Julien Lesca",
"Nicholas Mattei",
"Natan Kaminsky"
] | We propose a market-inspired bidding scheme for the assignment of paper reviews in large academic conferences. We provide an analysis of the incentives of reviewers during the bidding phase, when reviewers have both private costs and some information about the demand for each paper; and their goal is to obtain the best... | main | AI for Conference Organization and Delivery | 10.1609/aaai.v35i6.16609 | 35 | 6 | 4776-4784 | official | null | null |
10.1609/aaai.v35i6.16610 | A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences | https://ojs.aaai.org/index.php/AAAI/article/view/16610 | https://ojs.aaai.org/index.php/AAAI/article/download/16610/16417 | [
"Ivan Stelmakh",
"Nihar B. Shah",
"Aarti Singh",
"Hal Daumé III"
] | Conference peer review constitutes a human-computation process whose importance cannot be overstated: not only it identifies the best submissions for acceptance, but, ultimately, it impacts the future of the whole research area by promoting some ideas and restraining others. A surge in the number of submissions receive... | main | AI for Conference Organization and Delivery | 10.1609/aaai.v35i6.16610 | 35 | 6 | 4785-4793 | official | 2011.15050 | title_snapshot |
10.1609/aaai.v35i6.16611 | Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment | https://ojs.aaai.org/index.php/AAAI/article/view/16611 | https://ojs.aaai.org/index.php/AAAI/article/download/16611/16418 | [
"Ivan Stelmakh",
"Nihar B. Shah",
"Aarti Singh"
] | We consider the issue of strategic behaviour in various peer-assessment tasks, including peer grading of exams or homeworks and peer review in hiring or promotions. When a peer-assessment task is competitive (e.g., when students are graded on a curve), agents may be incentivized to misreport evaluations in order to imp... | main | AI for Conference Organization and Delivery | 10.1609/aaai.v35i6.16611 | 35 | 6 | 4794-4802 | official | 2010.04041 | title_snapshot |
10.1609/aaai.v35i6.16612 | Savable but Lost Lives when ICU Is Overloaded: a Model from 733 Patients in Epicenter Wuhan, China | https://ojs.aaai.org/index.php/AAAI/article/view/16612 | https://ojs.aaai.org/index.php/AAAI/article/download/16612/16419 | [
"Tingting Dan",
"Yang Li",
"Ziwei Zhu",
"Xijie Chen",
"Wuxiu Quan",
"Yu Hu",
"Guihua Tao",
"Lei Zhu",
"Jijin Zhu",
"Hongmin Cai",
"Hanchun Wen"
] | Coronavirus Disease 2019 (COVID-19) causes a sudden turnover to bad at some checkpoints and thus needs the intervention of intensive care unit (ICU). This resulted in urgent and large needs of ICUs posed great risks to the medical system. Estimating the mortality of critical in-patients who were not admitted into the I... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16612 | 35 | 6 | 4804-4811 | official | null | null |
10.1609/aaai.v35i6.16613 | Persistence of Anti-vaccine Sentiment in Social Networks Through Strategic Interactions | https://ojs.aaai.org/index.php/AAAI/article/view/16613 | https://ojs.aaai.org/index.php/AAAI/article/download/16613/16420 | [
"A S M Ahsan-Ul Haque",
"Mugdha Thakur",
"Matthew Bielskas",
"Achla Marathe",
"Anil Vullikanti"
] | Vaccination is the primary intervention for controlling the spread of infectious diseases. A certain level of vaccination rate (referred to as "herd immunity'') is needed for this intervention to be effective. However, there are concerns that herd immunity might not be achieved due to an increasing level of hesitancy a... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16613 | 35 | 6 | 4812-4820 | official | null | null |
10.1609/aaai.v35i6.16614 | Automated Model Design and Benchmarking of Deep Learning Models for COVID-19 Detection with Chest CT Scans | https://ojs.aaai.org/index.php/AAAI/article/view/16614 | https://ojs.aaai.org/index.php/AAAI/article/download/16614/16421 | [
"Xin He",
"Shihao Wang",
"Xiaowen Chu",
"Shaohuai Shi",
"Jiangping Tang",
"Xin Liu",
"Chenggang Yan",
"Jiyong Zhang",
"Guiguang Ding"
] | The COVID-19 pandemic has spread globally for several months. Because its transmissibility and high pathogenicity seriously threaten people's lives, it is crucial to accurately and quickly detect COVID-19 infection. Many recent studies have shown that deep learning (DL) based solutions can help detect COVID-19 based on... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16614 | 35 | 6 | 4821-4829 | official | 2101.05442 | title_judge |
10.1609/aaai.v35i6.16615 | STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization | https://ojs.aaai.org/index.php/AAAI/article/view/16615 | https://ojs.aaai.org/index.php/AAAI/article/download/16615/16422 | [
"Nikos Kargas",
"Cheng Qian",
"Nicholas D. Sidiropoulos",
"Cao Xiao",
"Lucas M. Glass",
"Jimeng Sun"
] | Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures. In this work, we develop a tensor method to predict the evolution of epidemic trends for many regions simultaneously. We construct a 3-way spatio-temporal tensor (location, attribute,... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16615 | 35 | 6 | 4830-4837 | official | 2012.04747 | title_snapshot |
10.1609/aaai.v35i6.16616 | Transfer Graph Neural Networks for Pandemic Forecasting | https://ojs.aaai.org/index.php/AAAI/article/view/16616 | https://ojs.aaai.org/index.php/AAAI/article/download/16616/16423 | [
"George Panagopoulos",
"Giannis Nikolentzos",
"Michalis Vazirgiannis"
] | The recent outbreak of COVID-19 has affected millions of individuals around the world and has posed a significant challenge to global healthcare. From the early days of the pandemic, it became clear that it is highly contagious and that human mobility contributes significantly to its spread. In this paper, we utilize g... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16616 | 35 | 6 | 4838-4845 | official | 2009.08388 | title_snapshot |
10.1609/aaai.v35i6.16617 | MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation | https://ojs.aaai.org/index.php/AAAI/article/view/16617 | https://ojs.aaai.org/index.php/AAAI/article/download/16617/16424 | [
"Yu Qiu",
"Yun Liu",
"Shijie Li",
"Jing Xu"
] | The rapid spread of the new pandemic, i.e., COVID-19, has severely threatened global health. Deep-learning-based computer-aided screening, e.g., COVID-19 infected CT area segmentation, has attracted much attention. However, the publicly available COVID-19 training data are limited, easily causing overfitting for tradit... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16617 | 35 | 6 | 4846-4854 | official | 2004.09750 | title_snapshot |
10.1609/aaai.v35i6.16618 | Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19 | https://ojs.aaai.org/index.php/AAAI/article/view/16618 | https://ojs.aaai.org/index.php/AAAI/article/download/16618/16425 | [
"Alexander Rodríguez",
"Nikhil Muralidhar",
"Bijaya Adhikari",
"Anika Tabassum",
"Naren Ramakrishnan",
"B. Aditya Prakash"
] | Forecasting influenza in a timely manner aids health organizations and policymakers in adequate preparation and decision making. However, effective influenza forecasting still remains a challenge despite increasing research interest. It is even more challenging amidst the COVID pandemic, when the influenza-like illness... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16618 | 35 | 6 | 4855-4863 | official | 2009.11407 | title_snapshot |
10.1609/aaai.v35i6.16619 | Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks | https://ojs.aaai.org/index.php/AAAI/article/view/16619 | https://ojs.aaai.org/index.php/AAAI/article/download/16619/16426 | [
"Arijit Sehanobish",
"Neal Ravindra",
"David Van Dijk"
] | A molecular and cellular understanding of how SARS-CoV-2 variably infects and causes severe COVID-19 remains a bottleneck in developing interventions to end the pandemic. We sought to use deep learning (DL) to study the biology of SARS-CoV-2 infection and COVID-19 severity by identifying transcriptomic patterns and cel... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16619 | 35 | 6 | 4864-4873 | official | 2006.12971 | title_snapshot |
10.1609/aaai.v35i6.16620 | Context Matters: Graph-based Self-supervised Representation Learning for Medical Images | https://ojs.aaai.org/index.php/AAAI/article/view/16620 | https://ojs.aaai.org/index.php/AAAI/article/download/16620/16427 | [
"Li Sun",
"Ke Yu",
"Kayhan Batmanghelich"
] | Supervised learning method requires a large volume of annotated datasets. Collecting such datasets is time-consuming and expensive. Until now, very few annotated COVID-19 imaging datasets are available. Although self-supervised learning enables us to bootstrap the training by exploiting unlabeled data, the generic self... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16620 | 35 | 6 | 4874-4882 | official | 2012.06457 | title_snapshot |
10.1609/aaai.v35i6.16621 | Tracking Disease Outbreaks from Sparse Data with Bayesian Inference | https://ojs.aaai.org/index.php/AAAI/article/view/16621 | https://ojs.aaai.org/index.php/AAAI/article/download/16621/16428 | [
"Bryan Wilder",
"Michael Mina",
"Milind Tambe"
] | The COVID-19 pandemic provides new motivation for a classic problem in epidemiology: estimating the empirical rate of transmission during an outbreak (formally, the time-varying reproduction number) from case counts. While standard methods exist, they work best at coarse-grained national or state scales with abundant d... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16621 | 35 | 6 | 4883-4891 | official | 2009.05863 | title_snapshot |
10.1609/aaai.v35i6.16622 | C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak | https://ojs.aaai.org/index.php/AAAI/article/view/16622 | https://ojs.aaai.org/index.php/AAAI/article/download/16622/16429 | [
"Congxi Xiao",
"Jingbo Zhou",
"Jizhou Huang",
"An Zhuo",
"Ji Liu",
"Haoyi Xiong",
"Dejing Dou"
] | The novel coronavirus disease (COVID-19) has crushed daily routines and is still rampaging through the world. Existing solution for nonpharmaceutical interventions usually needs to timely and precisely select a subset of residential urban areas for containment or even quarantine, where the spatial distribution of confi... | main | AI Responses to the COVID-19 Pandemic | 10.1609/aaai.v35i6.16622 | 35 | 6 | 4892-4900 | official | 2012.12169 | title_snapshot |
10.1609/aaai.v35i6.16632 | Explaining Neural Matrix Factorization with Gradient Rollback | https://ojs.aaai.org/index.php/AAAI/article/view/16632 | https://ojs.aaai.org/index.php/AAAI/article/download/16632/16439 | [
"Carolin Lawrence",
"Timo Sztyler",
"Mathias Niepert"
] | Explaining the predictions of neural black-box models is an important problem, especially when such models are used in applications where user trust is crucial. Estimating the influence of training examples on a learned neural model's behavior allows us to identify training examples most responsible for a given predict... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16632 | 35 | 6 | 4987-4995 | official | 2010.05516 | title_snapshot |
10.1609/aaai.v35i6.16640 | Adaptive Teaching of Temporal Logic Formulas to Preference-based Learners | https://ojs.aaai.org/index.php/AAAI/article/view/16640 | https://ojs.aaai.org/index.php/AAAI/article/download/16640/16447 | [
"Zhe Xu",
"Yuxin Chen",
"Ufuk Topcu"
] | Machine teaching is an algorithmic framework for teaching a target hypothesis via a sequence of examples or demonstrations. We investigate machine teaching for temporal logic formulas—a novel and expressive hypothesis class amenable to time-related task specifications. In the context of teaching temporal logic formulas... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16640 | 35 | 6 | 5061-5068 | official | 2001.09956 | title_judge |
10.1609/aaai.v35i6.16639 | Neural-Symbolic Integration: A Compositional Perspective | https://ojs.aaai.org/index.php/AAAI/article/view/16639 | https://ojs.aaai.org/index.php/AAAI/article/download/16639/16446 | [
"Efthymia Tsamoura",
"Timothy Hospedales",
"Loizos Michael"
] | Despite significant progress in the development of neural-symbolic frameworks, the question of how to integrate a neural and a symbolic system in a compositional manner remains open. Our work seeks to fill this gap by treating these two systems as black boxes to be integrated as modules into a single architecture, with... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16639 | 35 | 6 | 5051-5060 | official | 2010.11926 | title_snapshot |
10.1609/aaai.v35i6.16638 | Encoding Human Domain Knowledge to Warm Start Reinforcement Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16638 | https://ojs.aaai.org/index.php/AAAI/article/download/16638/16445 | [
"Andrew Silva",
"Matthew Gombolay"
] | Deep reinforcement learning has been successful in a variety of tasks, such as game playing and robotic manipulation. However, attempting to learn tabula rasa disregards the logical structure of many domains as well as the wealth of readily available knowledge from domain experts that could help "warm start" the learni... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16638 | 35 | 6 | 5042-5050 | official | 1902.06007 | title_judge |
10.1609/aaai.v35i6.16637 | Differentiable Inductive Logic Programming for Structured Examples | https://ojs.aaai.org/index.php/AAAI/article/view/16637 | https://ojs.aaai.org/index.php/AAAI/article/download/16637/16444 | [
"Hikaru Shindo",
"Masaaki Nishino",
"Akihiro Yamamoto"
] | The differentiable implementation of logic yields a seamless combination of symbolic reasoning and deep neural networks. Recent research, which has developed a differentiable framework to learn logic programs from examples, can even acquire reasonable solutions from noisy datasets. However, this framework severely limi... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16637 | 35 | 6 | 5034-5041 | official | 2103.01719 | title_snapshot |
10.1609/aaai.v35i6.16636 | Classification by Attention: Scene Graph Classification with Prior Knowledge | https://ojs.aaai.org/index.php/AAAI/article/view/16636 | https://ojs.aaai.org/index.php/AAAI/article/download/16636/16443 | [
"Sahand Sharifzadeh",
"Sina Moayed Baharlou",
"Volker Tresp"
] | A major challenge in scene graph classification is that the appearance of objects and relations can be significantly different from one image to another. Previous works have addressed this by relational reasoning over all objects in an image or incorporating prior knowledge into classification. Unlike previous works, w... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16636 | 35 | 6 | 5025-5033 | official | 2011.10084 | title_snapshot |
10.1609/aaai.v35i6.16635 | A Unified Framework for Planning with Learned Neural Network Transition Models | https://ojs.aaai.org/index.php/AAAI/article/view/16635 | https://ojs.aaai.org/index.php/AAAI/article/download/16635/16442 | [
"Buser Say"
] | Automated planning with neural network transition models is a two stage approach to solving planning problems with unknown transition models. The first stage of the approach learns the unknown transition model from data as a neural network model, and the second stage of the approach compiles the learned model to either... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16635 | 35 | 6 | 5016-5024 | official | null | null |
10.1609/aaai.v35i6.16634 | Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units | https://ojs.aaai.org/index.php/AAAI/article/view/16634 | https://ojs.aaai.org/index.php/AAAI/article/download/16634/16441 | [
"Ankur Mali",
"Alexander G. Ororbia",
"Daniel Kifer",
"C. Lee Giles"
] | Automated mathematical reasoning is a challenging problem that requires an agent to learn algebraic patterns that contain long-range dependencies. Two particular tasks that test this type of reasoning are (1)mathematical equation verification,which requires determining whether trigonometric and linear algebraic stateme... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16634 | 35 | 6 | 5006-5015 | official | 2104.02899 | title_snapshot |
10.1609/aaai.v35i6.16633 | A Scalable Reasoning and Learning Approach for Neural-Symbolic Stream Fusion | https://ojs.aaai.org/index.php/AAAI/article/view/16633 | https://ojs.aaai.org/index.php/AAAI/article/download/16633/16440 | [
"Danh Le-Phuoc",
"Thomas Eiter",
"Anh Le-Tuan"
] | Driven by deep neural networks (DNN), the recent development of computer vision makes vision sensors such as stereo cameras and Lidars ubiquitous in autonomous cars, robotics and traffic monitoring. However, a traditional DNN-based data fusion pipeline like object tracking has to hard-wire an engineered set of DNN mode... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16633 | 35 | 6 | 4996-5005 | official | null | null |
10.1609/aaai.v35i6.16623 | Conversational Neuro-Symbolic Commonsense Reasoning | https://ojs.aaai.org/index.php/AAAI/article/view/16623 | https://ojs.aaai.org/index.php/AAAI/article/download/16623/16430 | [
"Forough Arabshahi",
"Jennifer Lee",
"Mikayla Gawarecki",
"Kathryn Mazaitis",
"Amos Azaria",
"Tom Mitchell"
] | In order for conversational AI systems to hold more natural and broad-ranging conversations, they will require much more commonsense, including the ability to identify unstated presumptions of their conversational partners. For example, in the command "If it snows at night then wake me up early because I don't want to ... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16623 | 35 | 6 | 4902-4911 | official | 2006.10022 | title_snapshot |
10.1609/aaai.v35i6.16631 | Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic | https://ojs.aaai.org/index.php/AAAI/article/view/16631 | https://ojs.aaai.org/index.php/AAAI/article/download/16631/16438 | [
"Hunter Lang",
"Hoifung Poon"
] | Labeling training examples at scale is a perennial challenge in machine learning. Self-supervision methods compensate for the lack of direct supervision by leveraging prior knowledge to automatically generate noisy labeled examples. Deep probabilistic logic (DPL) is a unifying framework for self-supervised learning tha... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16631 | 35 | 6 | 4978-4986 | official | 2012.12474 | title_snapshot |
10.1609/aaai.v35i6.16630 | Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders | https://ojs.aaai.org/index.php/AAAI/article/view/16630 | https://ojs.aaai.org/index.php/AAAI/article/download/16630/16437 | [
"Bhushan Kotnis",
"Carolin Lawrence",
"Mathias Niepert"
] | Representation learning for knowledge graphs (KGs) has focused on the problem of answering simple link prediction queries. In this work we address the more ambitious challenge of predicting the answers of conjunctive queries with multiple missing entities. We propose Bidirectional Query Embedding (BiQE), a method that ... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16630 | 35 | 6 | 4968-4977 | official | 2004.02596 | title_snapshot |
10.1609/aaai.v35i6.16629 | Learning by Fixing: Solving Math Word Problems with Weak Supervision | https://ojs.aaai.org/index.php/AAAI/article/view/16629 | https://ojs.aaai.org/index.php/AAAI/article/download/16629/16436 | [
"Yining Hong",
"Qing Li",
"Daniel Ciao",
"Siyuan Huang",
"Song-Chun Zhu"
] | Previous neural solvers of math word problems (MWPs) are learned with full supervision and fail to generate diverse solutions. In this paper, we address this issue by introducing a weakly-supervised paradigm for learning MWPs. Our method only requires the annotations of the final answers and can generate various soluti... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16629 | 35 | 6 | 4959-4967 | official | 2012.10582 | title_snapshot |
10.1609/aaai.v35i6.16628 | Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers | https://ojs.aaai.org/index.php/AAAI/article/view/16628 | https://ojs.aaai.org/index.php/AAAI/article/download/16628/16435 | [
"Philipp Geiger",
"Christoph-Nikolas Straehle"
] | For prediction of interacting agents' trajectories, we propose an end-to-end trainable architecture that hybridizes neural nets with game-theoretic reasoning, has interpretable intermediate representations, and transfers to downstream decision making. It uses a net that reveals preferences from the agents' past joint t... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16628 | 35 | 6 | 4950-4958 | official | 2008.07303 | title_snapshot |
10.1609/aaai.v35i6.16627 | Planning from Pixels in Atari with Learned Symbolic Representations | https://ojs.aaai.org/index.php/AAAI/article/view/16627 | https://ojs.aaai.org/index.php/AAAI/article/download/16627/16434 | [
"Andrea Dittadi",
"Frederik K. Drachmann",
"Thomas Bolander"
] | Width-based planning methods have been shown to yield state-of-the-art performance in the Atari 2600 domain using pixel input. One successful approach, RolloutIW, represents states with the B-PROST boolean feature set. An augmented version of RolloutIW, pi-IW, shows that learned features can be competitive with handcra... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16627 | 35 | 6 | 4941-4949 | official | 2012.09126 | title_snapshot |
10.1609/aaai.v35i6.16626 | Aligning Artificial Neural Networks and Ontologies towards Explainable AI | https://ojs.aaai.org/index.php/AAAI/article/view/16626 | https://ojs.aaai.org/index.php/AAAI/article/download/16626/16433 | [
"Manuel De Sousa Ribeiro",
"João Leite"
] | Neural networks have been the key to solve a variety of different problems. However, neural network models are still regarded as black boxes, since they do not provide any human-interpretable evidence as to why they output a certain result. We address this issue by leveraging on ontologies and building small classifier... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16626 | 35 | 6 | 4932-4940 | official | null | null |
10.1609/aaai.v35i6.16625 | Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering | https://ojs.aaai.org/index.php/AAAI/article/view/16625 | https://ojs.aaai.org/index.php/AAAI/article/download/16625/16432 | [
"Antoine Bosselut",
"Ronan Le Bras",
"Yejin Choi"
] | Understanding narratives requires reasoning about implicit world knowledge related to the causes, effects, and states of situations described in text. At the core of this challenge is how to access contextually relevant knowledge on demand and reason over it. In this paper, we present initial studies toward zero-shot c... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16625 | 35 | 6 | 4923-4931 | official | 1911.03876 | title_snapshot |
10.1609/aaai.v35i6.16624 | Interpretable Actions: Controlling Experts with Understandable Commands | https://ojs.aaai.org/index.php/AAAI/article/view/16624 | https://ojs.aaai.org/index.php/AAAI/article/download/16624/16431 | [
"Shumeet Baluja",
"David Marwood",
"Michele Covell"
] | Despite the prevalence of deep neural networks, their single most cited drawback is that, even when successful, their operations are inscrutable. For many applications, the desired outputs are the composition of externally-defined bases. For such decomposable domains, we present a two-stage learning procedure producing... | main | Neuro-Symbolic AI | 10.1609/aaai.v35i6.16624 | 35 | 6 | 4912-4922 | official | null | null |
10.1609/aaai.v35i6.16729 | Power in Liquid Democracy | https://ojs.aaai.org/index.php/AAAI/article/view/16729 | https://ojs.aaai.org/index.php/AAAI/article/download/16729/16536 | [
"Yuzhe Zhang",
"Davide Grossi"
] | The paper develops a theory of power for delegable proxy voting systems. We define a power index able to measure the influence of both voters and delegators. Using this index, which we characterize axiomatically, we extend an earlier game-theoretic model by incorporating power-seeking behavior by agents. We analyticall... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16729 | 35 | 6 | 5822-5830 | official | 2010.07070 | title_snapshot |
10.1609/aaai.v35i6.16728 | Computing Ex Ante Coordinated Team-Maxmin Equilibria in Zero-Sum Multiplayer Extensive-Form Games | https://ojs.aaai.org/index.php/AAAI/article/view/16728 | https://ojs.aaai.org/index.php/AAAI/article/download/16728/16535 | [
"Youzhi Zhang",
"Bo An",
"Jakub Černý"
] | Computational game theory has many applications in the modern world in both adversarial situations and the optimization of social good. While there exist many algorithms for computing solutions in two-player interactions, finding optimal strategies in multiplayer interactions efficiently remains an open challenge. This... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16728 | 35 | 6 | 5813-5821 | official | 2009.12629 | title_snapshot |
10.1609/aaai.v35i6.16727 | Classification with Few Tests through Self-Selection | https://ojs.aaai.org/index.php/AAAI/article/view/16727 | https://ojs.aaai.org/index.php/AAAI/article/download/16727/16534 | [
"Hanrui Zhang",
"Yu Cheng",
"Vincent Conitzer"
] | We study test-based binary classification, where a principal either accepts or rejects agents based on the outcomes they get in a set of tests. The principal commits to a policy, which consists of all sets of outcomes that lead to acceptance. Each agent is modeled by a distribution over the space of possible outcomes. ... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16727 | 35 | 6 | 5805-5812 | official | null | null |
10.1609/aaai.v35i6.16726 | Incentive-Aware PAC Learning | https://ojs.aaai.org/index.php/AAAI/article/view/16726 | https://ojs.aaai.org/index.php/AAAI/article/download/16726/16533 | [
"Hanrui Zhang",
"Vincent Conitzer"
] | We study PAC learning in the presence of strategic manipulation, where data points may modify their features in certain predefined ways in order to receive a better outcome. We show that the vanilla ERM principle fails to achieve any nontrivial guarantee in this context. Instead, we propose an incentive-aware version o... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16726 | 35 | 6 | 5797-5804 | official | null | null |
10.1609/aaai.v35i6.16725 | Automated Mechanism Design for Classification with Partial Verification | https://ojs.aaai.org/index.php/AAAI/article/view/16725 | https://ojs.aaai.org/index.php/AAAI/article/download/16725/16532 | [
"Hanrui Zhang",
"Yu Cheng",
"Vincent Conitzer"
] | We study the problem of automated mechanism design with partial verification, where each type can (mis)report only a restricted set of types (rather than any other type), induced by the principal's limited verification power. We prove hardness results when the revelation principle does not necessarily hold, as well as ... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16725 | 35 | 6 | 5789-5796 | official | 2104.05182 | title_snapshot |
10.1609/aaai.v35i6.16724 | Finding and Certifying (Near-)Optimal Strategies in Black-Box Extensive-Form Games | https://ojs.aaai.org/index.php/AAAI/article/view/16724 | https://ojs.aaai.org/index.php/AAAI/article/download/16724/16531 | [
"Brian Hu Zhang",
"Tuomas Sandholm"
] | Often---for example in war games, strategy video games, and financial simulations---the game is given to us only as a black-box simulator in which we can play it. In these settings, since the game may have unknown nature action distributions (from which we can only obtain samples) and/or be too large to expand fully, i... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16724 | 35 | 6 | 5779-5788 | official | 2009.07384 | title_snapshot |
10.1609/aaai.v35i6.16723 | Targeted Negative Campaigning: Complexity and Approximations | https://ojs.aaai.org/index.php/AAAI/article/view/16723 | https://ojs.aaai.org/index.php/AAAI/article/download/16723/16530 | [
"Avishai Zagoury",
"Orgad Keller",
"Avinatan Hassidim",
"Noam Hazon"
] | Given the ubiquity of negative campaigning in recent political elections, we find it important to study its properties from a computational perspective. To this end, we present a model where elections can be manipulated by convincing voters to demote specific non-favored candidates, and study its properties in the clas... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16723 | 35 | 6 | 5768-5778 | official | null | null |
10.1609/aaai.v35i6.16712 | Estimating α-Rank by Maximizing Information Gain | https://ojs.aaai.org/index.php/AAAI/article/view/16712 | https://ojs.aaai.org/index.php/AAAI/article/download/16712/16519 | [
"Tabish Rashid",
"Cheng Zhang",
"Kamil Ciosek"
] | Game theory has been increasingly applied in settings where the game is not known outright, but has to be estimated by sampling. For example, meta-games that arise in multi-agent evaluation can only be accessed by running a succession of expensive experiments that may involve simultaneous deployment of several agents. ... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16712 | 35 | 6 | 5673-5681 | official | 2101.09178 | title_snapshot |
10.1609/aaai.v35i6.16708 | From Behavioral Theories to Econometrics: Inferring Preferences of Human Agents from Data on Repeated Interactions | https://ojs.aaai.org/index.php/AAAI/article/view/16708 | https://ojs.aaai.org/index.php/AAAI/article/download/16708/16515 | [
"Gali Noti"
] | We consider the problem of estimating preferences of human agents from data of strategic systems where the agents repeatedly interact. Recently, it was demonstrated that a new estimation method called "quantal regret" produces more accurate estimates for human agents than the classic approach that assumes that agents a... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16708 | 35 | 6 | 5637-5646 | official | 2112.15151 | title_snapshot |
10.1609/aaai.v35i6.16711 | A Permutation-Equivariant Neural Network Architecture For Auction Design | https://ojs.aaai.org/index.php/AAAI/article/view/16711 | https://ojs.aaai.org/index.php/AAAI/article/download/16711/16518 | [
"Jad Rahme",
"Samy Jelassi",
"Joan Bruna",
"S. Matthew Weinberg"
] | Designing an incentive compatible auction that maximizes expected revenue is a central problem in Auction Design. Theoretical approaches to the problem have hit some limits in the past decades and analytical solutions are known for only a few simple settings. Computational approaches to the problem through the use of L... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16711 | 35 | 6 | 5664-5672 | official | 2003.01497 | title_snapshot |
10.1609/aaai.v35i6.16710 | Market-Based Explanations of Collective Decisions | https://ojs.aaai.org/index.php/AAAI/article/view/16710 | https://ojs.aaai.org/index.php/AAAI/article/download/16710/16517 | [
"Dominik Peters",
"Grzegorz Pierczyński",
"Nisarg Shah",
"Piotr Skowron"
] | We consider approval-based committee elections, in which a size-k subset of available candidates must be selected given approval sets for each voter, indicating the candidates approved by the voter. A number of axioms capturing ideas of fairness and proportionality have been proposed for this framework. We argue that e... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16710 | 35 | 6 | 5656-5663 | official | null | null |
10.1609/aaai.v35i6.16709 | Preference Elicitation as Average-Case Sorting | https://ojs.aaai.org/index.php/AAAI/article/view/16709 | https://ojs.aaai.org/index.php/AAAI/article/download/16709/16516 | [
"Dominik Peters",
"Ariel D. Procaccia"
] | Many decision making systems require users to indicate their preferences via a ranking. It is common to elicit such rankings through pairwise comparison queries. By using sorting algorithms, this can be achieved by asking at most O(m log m) adaptive comparison queries. However, in many cases we have some advance (proba... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16709 | 35 | 6 | 5647-5655 | official | null | null |
10.1609/aaai.v35i6.16707 | Scarce Societal Resource Allocation and the Price of (Local) Justice | https://ojs.aaai.org/index.php/AAAI/article/view/16707 | https://ojs.aaai.org/index.php/AAAI/article/download/16707/16514 | [
"Quan Nguyen",
"Sanmay Das",
"Roman Garnett"
] | We consider the allocation of scarce societal resources, where a central authority decides which individuals receive which resources under capacity or budget constraints. Several algorithmic fairness criteria have been proposed to guide these procedures, each quantifying a notion of local justice to ensure the allocati... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16707 | 35 | 6 | 5628-5636 | official | null | null |
10.1609/aaai.v35i6.16706 | Fair and Efficient Allocations with Limited Demands | https://ojs.aaai.org/index.php/AAAI/article/view/16706 | https://ojs.aaai.org/index.php/AAAI/article/download/16706/16513 | [
"Sushirdeep Narayana",
"Ian A. Kash"
] | We study the fair division problem of allocating multiple resources among a set of agents with Leontief preferences that are each required to complete a finite amount of work, which we term "limited demands". We examine the behavior of the classic Dominant Resource Fairness (DRF) mechanism in this setting and show it i... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16706 | 35 | 6 | 5620-5627 | official | 2103.00391 | title_snapshot |
10.1609/aaai.v35i6.16705 | Majority Opinion Diffusion in Social Networks: An Adversarial Approach | https://ojs.aaai.org/index.php/AAAI/article/view/16705 | https://ojs.aaai.org/index.php/AAAI/article/download/16705/16512 | [
"Ahad N. Zehmakan"
] | We introduce and study a novel majority based opinion diffusion model. Consider a graph G, which represents a social network. Assume that initially a subset of nodes, called seed nodes or early adopters, are colored either black or white, which correspond to positive or negative opinion regarding a consumer product or ... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16705 | 35 | 6 | 5611-5619 | official | 2012.03143 | title_snapshot |
10.1609/aaai.v35i6.16704 | Coalition Formation in Multi-defender Security Games | https://ojs.aaai.org/index.php/AAAI/article/view/16704 | https://ojs.aaai.org/index.php/AAAI/article/download/16704/16511 | [
"Dolev Mutzari",
"Jiarui Gan",
"Sarit Kraus"
] | We study Stackelberg security game (SSG) with multiple defenders, where heterogeneous defenders need to allocate security resources to protect a set of targets against a strategic attacker. In such games, coordination and cooperation between the defenders can increase their ability to protect their assets, but the hete... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16704 | 35 | 6 | 5603-5610 | official | null | null |
10.1609/aaai.v35i6.16703 | On Fair and Efficient Allocations of Indivisible Goods | https://ojs.aaai.org/index.php/AAAI/article/view/16703 | https://ojs.aaai.org/index.php/AAAI/article/download/16703/16510 | [
"Aniket Murhekar",
"Jugal Garg"
] | We study the problem of fair and efficient allocation of a set of indivisible goods to agents with additive valuations using the popular fairness notions of envy-freeness up to one good (EF1) and equitability up to one good (EQ1) in conjunction with Pareto-optimality (PO). There exists a pseudo-polynomial time algorith... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16703 | 35 | 6 | 5595-5602 | official | null | null |
10.1609/aaai.v35i6.16714 | The Maximin Support Method: An Extension of the D’Hondt Method to Approval-Based Multiwinner Elections | https://ojs.aaai.org/index.php/AAAI/article/view/16714 | https://ojs.aaai.org/index.php/AAAI/article/download/16714/16521 | [
"Luis Sánchez-Fernández",
"Norberto Fernández García",
"Jesús A. Fisteus",
"Markus Brill"
] | We propose the maximin support method, a novel extension of the D'Hondt apportionment method to approval-based multiwinner elections. The maximin support method is a sequential procedure that aims to maximize the support of the least supported elected candidate. It can be computed efficiently and satisfies (adjusted ve... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16714 | 35 | 6 | 5690-5697 | official | 1609.05370 | title_snapshot |
10.1609/aaai.v35i6.16722 | A Model of Winners Allocation | https://ojs.aaai.org/index.php/AAAI/article/view/16722 | https://ojs.aaai.org/index.php/AAAI/article/download/16722/16529 | [
"Yongjie Yang"
] | We propose a model of winners allocation. In this model, we are given are two elections where the sets of candidates may intersect. The goal is to find two disjoint winning committees from respectively the two elections that are subjected to certain reasonable restrictions. For our model, we first propose several desir... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16722 | 35 | 6 | 5760-5767 | official | null | null |
10.1609/aaai.v35i6.16721 | If You Like Shapley Then You’ll Love the Core | https://ojs.aaai.org/index.php/AAAI/article/view/16721 | https://ojs.aaai.org/index.php/AAAI/article/download/16721/16528 | [
"Tom Yan",
"Ariel D. Procaccia"
] | The prevalent approach to problems of credit assignment in machine learning -- such as feature and data valuation -- is to model the problem at hand as a cooperative game and apply the Shapley value. But cooperative game theory offers a rich menu of alternative solution concepts, which famously includes the core and it... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16721 | 35 | 6 | 5751-5759 | official | null | null |
10.1609/aaai.v35i6.16720 | The Smoothed Complexity of Computing Kemeny and Slater Rankings | https://ojs.aaai.org/index.php/AAAI/article/view/16720 | https://ojs.aaai.org/index.php/AAAI/article/download/16720/16527 | [
"Lirong Xia",
"Weiqiang Zheng"
] | The computational complexity of winner determination under common voting rules is a classical and fundamental topic in the field of computational social choice. Previous work has established the NP-hardness of winner determination under some commonly-studied voting rules, such as the Kemeny rule and the Slater rule. In... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16720 | 35 | 6 | 5742-5750 | official | 2010.13020 | title_snapshot |
10.1609/aaai.v35i6.16719 | Facility’s Perspective to Fair Facility Location Problems | https://ojs.aaai.org/index.php/AAAI/article/view/16719 | https://ojs.aaai.org/index.php/AAAI/article/download/16719/16526 | [
"Chenhao Wang",
"Xiaoying Wu",
"Minming Li",
"Hau Chan"
] | We study the problem faced by a decision maker who wants to locate a set of facilities on a real line and allocate agents/items to the facilities. The items have given locations on the line, and can only be assigned to one of their closest facilities. The facilities are controlled by managers, who have additive utility... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16719 | 35 | 6 | 5734-5741 | official | null | null |
10.1609/aaai.v35i6.16718 | Restricted Domains of Dichotomous Preferences with Possibly Incomplete Information | https://ojs.aaai.org/index.php/AAAI/article/view/16718 | https://ojs.aaai.org/index.php/AAAI/article/download/16718/16525 | [
"Zoi Terzopoulou",
"Alexander Karpov",
"Svetlana Obraztsova"
] | Restricted domains over voter preferences have been extensively studied within the area of computational social choice, initially for preferences that are total orders over the set of alternatives and subsequently for preferences that are dichotomous—i.e., that correspond to approved and disapproved alternatives. This ... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16718 | 35 | 6 | 5726-5733 | official | null | null |
10.1609/aaai.v35i6.16713 | Online Posted Pricing with Unknown Time-Discounted Valuations | https://ojs.aaai.org/index.php/AAAI/article/view/16713 | https://ojs.aaai.org/index.php/AAAI/article/download/16713/16520 | [
"Giulia Romano",
"Gianluca Tartaglia",
"Alberto Marchesi",
"Nicola Gatti"
] | We study the problem of designing posted-price mechanisms in order to sell a single unit of a single item within a finite period of time. Motivated by real-world problems, such as, e.g., long-term rental of rooms and apartments, we assume that customers arrive online according to a Poisson process, and their valuations... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16713 | 35 | 6 | 5682-5689 | official | 2012.05774 | title_snapshot |
10.1609/aaai.v35i6.16717 | Coupon Design in Advertising Systems | https://ojs.aaai.org/index.php/AAAI/article/view/16717 | https://ojs.aaai.org/index.php/AAAI/article/download/16717/16524 | [
"Weiran Shen",
"Pingzhong Tang",
"Xun Wang",
"Yadong Xu",
"Xiwang Yang"
] | Online platforms sell advertisements via auctions (e.g., VCG and GSP auction) and revenue maximization is one of the most important tasks for them. Many revenue increment methods are proposed, like reserve pricing, boosting, coupons and so on. The novelty of coupons rests on the fact that coupons are optional for adver... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16717 | 35 | 6 | 5717-5725 | official | null | null |
10.1609/aaai.v35i6.16716 | Modeling Voters in Multi-Winner Approval Voting | https://ojs.aaai.org/index.php/AAAI/article/view/16716 | https://ojs.aaai.org/index.php/AAAI/article/download/16716/16523 | [
"Jaelle Scheuerman",
"Jason Harman",
"Nicholas Mattei",
"K. Brent Venable"
] | In many real world situations, collective decisions are made using voting and, in scenarios such as committee or board elections, employing voting rules that return multiple winners. In multi-winner approval voting (AV), an agent submits a ballot consisting of approvals for as many candidates as they wish, and winners ... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16716 | 35 | 6 | 5709-5716 | official | 2012.02811 | title_snapshot |
10.1609/aaai.v35i6.16715 | Solution Concepts in Hierarchical Games Under Bounded Rationality With Applications to Autonomous Driving | https://ojs.aaai.org/index.php/AAAI/article/view/16715 | https://ojs.aaai.org/index.php/AAAI/article/download/16715/16522 | [
"Atrisha Sarkar",
"Krzysztof Czarnecki"
] | With autonomous vehicles (AV) set to integrate further into regular human traffic, there is an increasing consensus of treating AV motion planning as a multi-agent problem. However, the traditional game theoretic assumption of complete rationality is too strong for the purpose of human driving, and there is a need for ... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16715 | 35 | 6 | 5698-5708 | official | 2009.10033 | title_snapshot |
10.1609/aaai.v35i6.16686 | An Analysis of Approval-Based Committee Rules for 2D-Euclidean Elections | https://ojs.aaai.org/index.php/AAAI/article/view/16686 | https://ojs.aaai.org/index.php/AAAI/article/download/16686/16493 | [
"Michał T. Godziszewski",
"Paweł Batko",
"Piotr Skowron",
"Piotr Faliszewski"
] | We study approval-based committee elections for the case where the voters' preferences come from a 2D-Euclidean model. We consider two main issues: First, we ask for the complexity of computing election results. Second, we evaluate election outcomes experimentally, following the visualization technique of Elkind et al.... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16686 | 35 | 6 | 5448-5455 | official | null | null |
10.1609/aaai.v35i6.16687 | Aggregating Binary Judgments Ranked by Accuracy | https://ojs.aaai.org/index.php/AAAI/article/view/16687 | https://ojs.aaai.org/index.php/AAAI/article/download/16687/16494 | [
"Daniel Halpern",
"Gregory Kehne",
"Dominik Peters",
"Ariel D. Procaccia",
"Nisarg Shah",
"Piotr Skowron"
] | We revisit the fundamental problem of predicting a binary ground truth based on independent binary judgments provided by experts. When the accuracy levels of the experts are known, the problem can be solved easily through maximum likelihood estimation. We consider, however, a setting in which we are given only a rankin... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16687 | 35 | 6 | 5456-5463 | official | null | null |
10.1609/aaai.v35i6.16688 | District-Fair Participatory Budgeting | https://ojs.aaai.org/index.php/AAAI/article/view/16688 | https://ojs.aaai.org/index.php/AAAI/article/download/16688/16495 | [
"D Ellis Hershkowitz",
"Anson Kahng",
"Dominik Peters",
"Ariel D. Procaccia"
] | Participatory budgeting is a method used by city governments to select public projects to fund based on residents' votes. Many cities use participatory budgeting at a district level. Typically, a budget is divided among districts proportionally to their population, and each district holds an election over local project... | main | Game Theory and Economic Paradigms | 10.1609/aaai.v35i6.16688 | 35 | 6 | 5464-5471 | official | 2102.06115 | title_snapshot |
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