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official:AAAI:8ac4ea16db9ab72712b959fa | 10.1609/aaai.v31i1.10703 | Solving Seven Open Problems of Offline and Online Control in Borda Elections | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Marc Neveling", "affiliations": []}, {"id": null, "name": "Jörg Rothe", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Standard (offline) control scenarios in elections (such as adding, deleting, or partitioning either voters or candidates) have been studied for many voting systems, natural and less natural ones, and the related control problems have been classified in terms of their complexity. However, for one of the most important n... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10703", "DOI": "10.1609/aaai.v31i1.10703"} | ["Computer Science"] |
official:AAAI:4072e49f449ff93c5fad9548 | 10.1609/aaai.v31i1.11034 | Incorporating Domain-Independent Planning Heuristics in Hierarchical Planning | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Vikas Shivashankar", "affiliations": []}, {"id": null, "name": "Ron Alford", "affiliations": []}, {"id": null, "name": "David Aha", "affiliations": []}] | null | [] | Computer Science | null | null | true | null | Heuristics serve as a powerful tool in modern domain-independent planning (DIP) systems by providing critical guidance during the search for high-quality solutions. However, they have not been broadly used with hierarchical planning techniques, which are more expressive and tend to scale better in complex domains by ex... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11034", "DOI": "10.1609/aaai.v31i1.11034"} | ["Computer Science"] |
official:AAAI:6185d13fc2930b954e33043d | 10.1609/aaai.v31i1.10650 | Embedded Bandits for Large-Scale Black-Box Optimization | 2,017 | null | ["ConferencePaper"] | 0 | AAAI | [{"id": null, "name": "Abdullah Al-Dujaili", "affiliations": []}, {"id": null, "name": "S. Suresh", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Random embedding has been applied with empirical success to large-scale black-box optimization problems with low effective dimensions. This paper proposes the EmbeddedHunter algorithm, which incorporates the technique in a hierarchical stochastic bandit setting, following the optimism in the face of uncertainty princip... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10650", "DOI": "10.1609/aaai.v31i1.10650"} | ["Computer Science"] |
official:AAAI:c1cbee593901926ead0a83d8 | 10.1609/aaai.v31i1.11087 | Enhancing the Privacy of Predictors | 2,017 | null | ["ConferencePaper"] | 0 | AAAI | [{"id": null, "name": "Ke Xu", "affiliations": []}, {"id": null, "name": "Swair Shah", "affiliations": []}, {"id": null, "name": "Tongyi Cao", "affiliations": []}, {"id": null, "name": "Crystal Maung", "affiliations": []}, {"id": null, "name": "Haim Schweitzer", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | The privacy challenge considered here is to prevent an adversary from using available feature values to predict confi- dential information. We propose an algorithm providing such privacy for predictors that have a linear operator in the first stage. Privacy is achieved by zeroing out feature components in the approxima... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11087", "DOI": "10.1609/aaai.v31i1.11087"} | ["Computer Science"] |
official:AAAI:abd1832a5145381d46995dbf | 10.1609/aaai.v31i1.10565 | Optimal Personalized Defense Strategy Against Man-In-The-Middle Attack | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Xiaohong Li", "affiliations": []}, {"id": null, "name": "Shuxin Li", "affiliations": []}, {"id": null, "name": "Jianye Hao", "affiliations": []}, {"id": null, "name": "Zhiyong Feng", "affiliations": []}, {"id": null, "name": "Bo An", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | The Man-In-The-Middle (MITM) attack is one of the most common attacks employed in the network hacking. MITM attackers can successfully invoke attacks such as denial of service (DoS) and port stealing, and lead to surprisingly harmful consequences for users in terms of both financial loss and security issues. The conven... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10565", "DOI": "10.1609/aaai.v31i1.10565"} | ["Computer Science"] |
official:AAAI:a0c7b0d9994e60dc24a494f8 | 10.1609/aaai.v31i1.11229 | Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification | 2,017 | null | ["ConferencePaper"] | 81 | AAAI | [{"id": null, "name": "Emily Hand", "affiliations": []}, {"id": null, "name": "Rama Chellappa", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Attributes, or mid-level semantic features, have gained popularity in the past few years in domains ranging from activity recognition to face verification. Improving the accuracy of attribute classifiers is an important first step in any application which uses these attributes. In most works to date, attributes have be... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11229", "DOI": "10.1609/aaai.v31i1.11229"} | ["Computer Science"] |
official:AAAI:25bb09d58890b5897305cfc2 | 10.1609/aaai.v31i1.11198 | Reference Based LSTM for Image Captioning | 2,017 | null | ["ConferencePaper"] | 38 | AAAI | [{"id": null, "name": "Minghai Chen", "affiliations": []}, {"id": null, "name": "Guiguang Ding", "affiliations": []}, {"id": null, "name": "Sicheng Zhao", "affiliations": []}, {"id": null, "name": "Hui Chen", "affiliations": []}, {"id": null, "name": "Qiang Liu", "affiliations": []}, {"id": null, "name": "Jungong Han",... | null | [] | Computer Science | null | null | false | benchmark dataset | Image captioning is an important problem in artificial intelligence, related to both computer vision and natural language processing. There are two main problems in existing methods: in the training phase, it is difficult to find which parts of the captions are more essential to the image; in the caption generation pha... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11198", "DOI": "10.1609/aaai.v31i1.11198"} | ["Computer Science"] |
official:AAAI:487268074891bb6420e00b12 | 10.1609/aaai.v31i1.10482 | Finding Critical Users for Social Network Engagement: The Collapsed k-Core Problem | 2,017 | null | ["ConferencePaper"] | 57 | AAAI | [{"id": null, "name": "Fan Zhang", "affiliations": []}, {"id": null, "name": "Ying Zhang", "affiliations": []}, {"id": null, "name": "Lu Qin", "affiliations": []}, {"id": null, "name": "Wenjie Zhang", "affiliations": []}, {"id": null, "name": "Xuemin Lin", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In social networks, the leave of critical users may significantly break network engagement, i.e., lead a large number of other users to drop out. A popular model to measure social network engagement is k-core, the maximal induced subgraph in which every vertex has at least k neighbors. To identify critical users for so... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10482", "DOI": "10.1609/aaai.v31i1.10482"} | ["Computer Science"] |
official:AAAI:d1ca8281125facd1d8318140 | 10.1609/aaai.v31i2.19097 | Determining Relative Airport Threats from News and Social Media | 2,017 | null | ["ConferencePaper"] | 4 | AAAI | [{"id": null, "name": "Rupinder Khandpur", "affiliations": []}, {"id": null, "name": "Taoran Ji", "affiliations": []}, {"id": null, "name": "Yue Ning", "affiliations": []}, {"id": null, "name": "Liang Zhao", "affiliations": []}, {"id": null, "name": "Chang-Tien Lu", "affiliations": []}, {"id": null, "name": "Erik Smith... | null | [] | Computer Science | null | null | false | null | Airports are a prime target for terrorist organizations, drug traffickers, smugglers, and other nefarious groups. Traditional forms of security assessment are not real-time and often do not exist for each airport and port of entry. Thus, homeland security professionals must rely on measures of attractiveness of an airp... | C | {"URL": "https://doi.org/10.1609/aaai.v31i2.19097", "DOI": "10.1609/aaai.v31i2.19097"} | ["Computer Science"] |
official:AAAI:c71e17e8667bdac3ec08c83e | 10.1609/aaai.v31i1.11144 | null | 2,017 | 2016-10-01 | ["ConferencePaper"] | 3 | AAAI | [{"id": null, "name": "Nevin Zhang", "affiliations": []}, {"id": null, "name": "Leonard Poon", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Latent tree analysis seeks to model the correlations amonga set of random variables using a tree of latent variables. It was proposed as an improvement to latent class analysis-a method widely used in social sciences and medicine to identify homogeneous subgroups in a population. It provides new and fruitful perspectiv... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11144", "DOI": "10.1609/aaai.v31i1.11144", "ArXiv": "1610.00085", "S2": "a275f6092e9569dfd0edcf9a8937e700309cdede", "OpenAlex": "W4295205890"} | ["Computer Science"] |
official:AAAI:273a2d52a3a930d6056434bc | 10.1609/aaai.v31i1.10865 | Active Search for Sparse Signals with Region Sensing | 2,017 | null | ["ConferencePaper"] | 6 | AAAI | [{"id": null, "name": "Yifei Ma", "affiliations": []}, {"id": null, "name": "Roman Garnett", "affiliations": []}, {"id": null, "name": "Jeff Schneider", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Autonomous systems can be used to search for sparse signals in a large space; e.g., aerial robots can be deployed to localize threats, detect gas leaks, or respond to distress calls. Intuitively, search algorithms may increase efficiency by collecting aggregate measurements summarizing large contiguous regions. However... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10865", "DOI": "10.1609/aaai.v31i1.10865"} | ["Computer Science"] |
official:AAAI:1b1c7d3e1b87a962e28771ea | 10.1609/aaai.v31i1.11207 | Robust Visual Tracking via Local-Global Correlation Filter | 2,017 | null | ["ConferencePaper"] | 9 | AAAI | [{"id": null, "name": "Heng Fan", "affiliations": []}, {"id": null, "name": "Jinhai Xiang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Correlation filter has drawn increasing interest in visual tracking due to its high efficiency, however, it is sensitive to partial occlusion, which may result in tracking failure. To address this problem, we propose a novel local-global correlation filter (LGCF) for object tracking. Our LGCF model utilizes both local-... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11207", "DOI": "10.1609/aaai.v31i1.11207"} | ["Computer Science"] |
official:AAAI:a30c94cf453152942a553745 | 10.1609/aaai.v31i1.11180 | Spatial Projection of Multiple Climate Variables Using Hierarchical Multitask Learning | 2,017 | null | ["ConferencePaper"] | 3 | AAAI | [{"id": null, "name": "Andre Goncalves", "affiliations": []}, {"id": null, "name": "Arindam Banerjee", "affiliations": []}, {"id": null, "name": "Fernando Von Zuben", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Future projection of climate is typically obtained by combining outputs from multiple Earth System Models (ESMs) for several climate variables such as temperature and precipitation. While IPCC has traditionally used a simple model output average, recent work has illustrated potential advantages of using a multitask lea... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11180", "DOI": "10.1609/aaai.v31i1.11180"} | ["Computer Science"] |
official:AAAI:807426c04c65b25b6602149b | 10.1609/aaai.v31i1.10580 | Axiomatic Characterization of Game-Theoretic Network Centralities | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Oskar Skibski", "affiliations": []}, {"id": null, "name": "Tomasz Michalak", "affiliations": []}, {"id": null, "name": "Talal Rahwan", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | One of the fundamental research challenges in network science is the centrality analysis, i.e., identifying the nodes that play the most important roles in the network. In this paper, we focus on the game-theoretic approach to centrality analysis. While various centrality indices have been proposed based on this approa... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10580", "DOI": "10.1609/aaai.v31i1.10580"} | ["Computer Science"] |
official:AAAI:c3812bb27280a7a3408d8d65 | 10.1609/aaai.v31i1.10790 | Beyond RPCA: Flattening Complex Noise in the Frequency Domain | 2,017 | null | ["ConferencePaper"] | 5 | AAAI | [{"id": null, "name": "Yunhe Wang", "affiliations": []}, {"id": null, "name": "Chang Xu", "affiliations": []}, {"id": null, "name": "Chao Xu", "affiliations": []}, {"id": null, "name": "Dacheng Tao", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Discovering robust low-rank data representations is important in many real-world problems. Traditional robust principal component analysis (RPCA) assumes that the observed data are corrupted by some sparse noise (e.g., Laplacian noise) and utilizes the l1-norm to separate out the noisy compo- nent. Nevertheless, as wel... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10790", "DOI": "10.1609/aaai.v31i1.10790"} | ["Computer Science"] |
official:AAAI:d58fdcf2fc031e6403bd2075 | 10.1609/aaai.v31i1.10831 | Asymmetric Discrete Graph Hashing | 2,017 | null | ["ConferencePaper"] | 23 | AAAI | [{"id": null, "name": "Xiaoshuang Shi", "affiliations": []}, {"id": null, "name": "Fuyong Xing", "affiliations": []}, {"id": null, "name": "Kaidi Xu", "affiliations": []}, {"id": null, "name": "Manish Sapkota", "affiliations": []}, {"id": null, "name": "Lin Yang", "affiliations": []}] | null | [] | Computer Science | null | null | true | null | Recently, many graph based hashing methods have been emerged to tackle large-scale problems. However, there exists two major bottlenecks: (1) directly learning discrete hashing codes is an NP-hardoptimization problem; (2) the complexity of both storage and computational time to build a graph with n data points is O(n2)... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10831", "DOI": "10.1609/aaai.v31i1.10831"} | ["Computer Science"] |
official:AAAI:2b5b7640e09b9381c3615859 | 10.1609/aaai.v31i1.10945 | Where to Add Actions in Human-in-the-Loop Reinforcement Learning | 2,017 | null | ["ConferencePaper"] | 22 | AAAI | [{"id": null, "name": "Travis Mandel", "affiliations": []}, {"id": null, "name": "Yun-En Liu", "affiliations": []}, {"id": null, "name": "Emma Brunskill", "affiliations": []}, {"id": null, "name": "Zoran Popović", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In order for reinforcement learning systems to learn quickly in vast action spaces such as the space of all possible pieces of text or the space of all images, leveraging human intuition and creativity is key. However, a human-designed action space is likely to be initially imperfect and limited; furthermore, humans ma... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10945", "DOI": "10.1609/aaai.v31i1.10945"} | ["Computer Science"] |
official:AAAI:4f58a81149824751bdd4bb49 | 10.1609/aaai.v31i1.10651 | Parallel Asynchronous Stochastic Variance Reduction for Nonconvex Optimization | 2,017 | null | ["ConferencePaper"] | 4 | AAAI | [{"id": null, "name": "Cong Fang", "affiliations": []}, {"id": null, "name": "Zhouchen Lin", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Nowadays, asynchronous parallel algorithms have received much attention in the optimization field due to the crucial demands for modern large-scale optimization problems. However, most asynchronous algorithms focus on convex problems. Analysis on nonconvex problems is lacking. For the Asynchronous Stochastic Descent (A... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10651", "DOI": "10.1609/aaai.v31i1.10651"} | ["Computer Science"] |
official:AAAI:9207e5a8e5132e84008a085e | 10.1609/aaai.v31i1.10897 | Thompson Sampling for Stochastic Bandits with Graph Feedback | 2,017 | null | ["ConferencePaper"] | 4 | AAAI | [{"id": null, "name": "Aristide Tossou", "affiliations": []}, {"id": null, "name": "Christos Dimitrakakis", "affiliations": []}, {"id": null, "name": "Devdatt Dubhashi", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We present a simple set of algorithms based on Thompson Sampling for stochastic bandit problems with graph feedback. Thompson Sampling is generally applicable, without the need to construct complicated upper confidence bounds. As we show in this paper, it has excellent performance in problems with graph feedback, even ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10897", "DOI": "10.1609/aaai.v31i1.10897"} | ["Computer Science"] |
official:AAAI:e79e542544e883a6f642d871 | 10.1609/aaai.v31i1.10667 | Anytime Anyspace AND/OR Search for Bounding the Partition Function | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Qi Lou", "affiliations": []}, {"id": null, "name": "Rina Dechter", "affiliations": []}, {"id": null, "name": "Alexander Ihler", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Bounding the partition function is a key inference task in many graphical models. In this paper, we develop an anytime anyspace search algorithm taking advantage of AND/OR tree structure and optimized variational heuristics to tighten deterministic bounds on the partition function. We study how our priority-driven best... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10667", "DOI": "10.1609/aaai.v31i1.10667"} | ["Computer Science"] |
official:AAAI:74041812c6b79fe1d80ed52e | 10.1609/aaai.v31i1.11079 | Chaotic Time Series Prediction Using a Photonic Reservoir Computer with Output Feedback | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Piotr Antonik", "affiliations": []}, {"id": null, "name": "Michiel Hermans", "affiliations": []}, {"id": null, "name": "Marc Haelterman", "affiliations": []}, {"id": null, "name": "Serge Massar", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals (Jaeger andHaas 2004; Maass, Natschlager, and Markram 2002). It canbe easily implemented in hardware. The performance ofthese analogue devices matches digital algorithms on a series of benchmark tasks (see e.g. (Soriano et al... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11079", "DOI": "10.1609/aaai.v31i1.11079"} | ["Computer Science"] |
official:AAAI:cc6a94b58fcc3e34e9c8c8f0 | 10.1609/aaai.v31i1.11217 | Fully Convolutional Neural Networks with Full-Scale-Features for Semantic Segmentation | 2,017 | null | ["ConferencePaper"] | 8 | AAAI | [{"id": null, "name": "Tianxiang Pan", "affiliations": []}, {"id": null, "name": "Bin Wang", "affiliations": []}, {"id": null, "name": "Guiguang Ding", "affiliations": []}, {"id": null, "name": "Jun-Hai Yong", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In this work, we propose a novel method to involve full-scale-features into the fully convolutional neural networks (FCNs) for Semantic Segmentation. Current works on FCN has brought great advances in the task of semantic segmentation, but the receptive field, which represents region areas of input volume connected to ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11217", "DOI": "10.1609/aaai.v31i1.11217"} | ["Computer Science"] |
official:AAAI:3b69cf8912001e86583b3b6e | 10.1609/aaai.v31i1.11112 | Multimodal Fusion of EEG and Musical Features in Music-Emotion Recognition | 2,017 | null | ["ConferencePaper"] | 12 | AAAI | [{"id": null, "name": "Nattapong Thammasan", "affiliations": []}, {"id": null, "name": "Ken-ichi Fukui", "affiliations": []}, {"id": null, "name": "Masayuki Numao", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Multimodality has been recently exploited to overcome the challenges of emotion recognition. In this paper, we present a study of fusion of electroencephalogram (EEG) features and musical features extracted from musical stimuli at decision level in recognizing the time-varying binary classes of arousal and valence. Our... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11112", "DOI": "10.1609/aaai.v31i1.11112"} | ["Computer Science"] |
official:AAAI:25d399c11d4fdfab7e7b39b2 | 10.1609/aaai.v31i1.11123 | Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation | 2,017 | null | ["ConferencePaper"] | 16 | AAAI | [{"id": null, "name": "Josiah Hanna", "affiliations": []}, {"id": null, "name": "Peter Stone", "affiliations": []}, {"id": null, "name": "Scott Niekum", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In many reinforcement learning applications, it is desirable to determine confidence interval lower bounds on the performance of any given policy without executing said policy. In this context, we propose two bootstrapping off-policy evaluation methods which use learned MDP transition models in order to estimate lower ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11123", "DOI": "10.1609/aaai.v31i1.11123"} | ["Computer Science"] |
official:AAAI:7bc8d897573212b44b037388 | 10.1609/aaai.v31i1.10977 | A Unified Model for Cross-Domain and Semi-Supervised Named Entity Recognition in Chinese Social Media | 2,017 | null | ["ConferencePaper"] | 65 | AAAI | [{"id": null, "name": "Hangfeng He", "affiliations": []}, {"id": null, "name": "Xu Sun", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Named entity recognition (NER) in Chinese social media is important but difficult because of its informality and strong noise. Previous methods only focus on in-domain supervised learning which is limited by the rare annotated data. However, there are enough corpora in formal domains and massive in-domain unannotated t... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10977", "DOI": "10.1609/aaai.v31i1.10977"} | ["Computer Science"] |
official:AAAI:7e31234f45036c228ac9c1a3 | 10.1609/aaai.v31i1.10893 | Multiple Kernel k-Means with Incomplete Kernels | 2,017 | null | ["ConferencePaper"] | 32 | AAAI | [{"id": null, "name": "Xinwang Liu", "affiliations": []}, {"id": null, "name": "Miaomiao Li", "affiliations": []}, {"id": null, "name": "Lei Wang", "affiliations": []}, {"id": null, "name": "Yong Dou", "affiliations": []}, {"id": null, "name": "Jianping Yin", "affiliations": []}, {"id": null, "name": "En Zhu", "affilia... | null | [] | Computer Science | null | null | false | null | Multiple kernel clustering (MKC) algorithms optimally combine a group of pre-specified base kernels to improve clustering performance. However, existing MKC algorithms cannot efficiently address the situation where some rows and columns of base kernels are absent. This paper proposes a simple while effective algorithm ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10893", "DOI": "10.1609/aaai.v31i1.10893"} | ["Computer Science"] |
official:AAAI:5184cfa0da0dd786de9e4832 | 10.1609/aaai.v31i1.10895 | Optimal Neighborhood Kernel Clustering with Multiple Kernels | 2,017 | null | ["ConferencePaper"] | 75 | AAAI | [{"id": null, "name": "Xinwang Liu", "affiliations": []}, {"id": null, "name": "Sihang Zhou", "affiliations": []}, {"id": null, "name": "Yueqing Wang", "affiliations": []}, {"id": null, "name": "Miaomiao Li", "affiliations": []}, {"id": null, "name": "Yong Dou", "affiliations": []}, {"id": null, "name": "En Zhu", "affi... | null | [] | Computer Science | null | null | false | null | Multiple kernel $k$-means (MKKM) aims to improve clustering performance by learning an optimal kernel, which is usually assumed to be a linear combination of a group of pre-specified base kernels. However, we observe that this assumption could: i) cause limited kernel representation capability; and ii) not sufficiently... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10895", "DOI": "10.1609/aaai.v31i1.10895"} | ["Computer Science"] |
official:AAAI:1c78c9847bd0f8ec084745c8 | 10.1609/aaai.v31i1.11212 | An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data | 2,017 | null | ["ConferencePaper"] | 558 | AAAI | [{"id": null, "name": "Sijie Song", "affiliations": []}, {"id": null, "name": "Cuiling Lan", "affiliations": []}, {"id": null, "name": "Junliang Xing", "affiliations": []}, {"id": null, "name": "Wenjun Zeng", "affiliations": []}, {"id": null, "name": "Jiaying Liu", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Human action recognition is an important task in computer vision. Extracting discriminative spatial and temporal features to model the spatial and temporal evolutions of different actions plays a key role in accomplishing this task. In this work, we propose an end-to-end spatial and temporal attention model for human a... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11212", "DOI": "10.1609/aaai.v31i1.11212"} | ["Computer Science"] |
official:AAAI:59283326424b9a51ce312b10 | 10.1609/aaai.v31i1.11097 | Semantic Representation Using Explicit Concept Space Models | 2,017 | null | ["ConferencePaper"] | 0 | AAAI | [{"id": null, "name": "Walid Shalaby", "affiliations": []}, {"id": null, "name": "Wlodek Zadrozny", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Explicit concept space models have proven efficacy for text representation in many natural language and text mining applications. The idea is to embed textual structures into a semantic space of concepts which captures the main topics of these structures. Despite their wide applicability, existing models have many shor... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11097", "DOI": "10.1609/aaai.v31i1.11097"} | ["Computer Science"] |
official:AAAI:3b8fbc8abd6d714112b36b3d | 10.1609/aaai.v31i1.11031 | Logical Filtering and Smoothing: State Estimation in Partially Observable Domains | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Brent Mombourquette", "affiliations": []}, {"id": null, "name": "Christian Muise", "affiliations": []}, {"id": null, "name": "Sheila McIlraith", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | State estimation is the task of estimating the state of a partially observable dynamical system given a sequence of executed actions and observations. In logical settings, state estimation can be realized via logical filtering, which is exact but can be intractable. We propose logical smoothing, a form of backwards rea... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11031", "DOI": "10.1609/aaai.v31i1.11031"} | ["Computer Science"] |
official:AAAI:e2ded3f022aeed7c75a6d482 | 10.1609/aaai.v31i1.11018 | Validating Domains and Plans for Temporal Planning via Encoding into Infinite-State Linear Temporal Logic | 2,017 | null | ["ConferencePaper"] | 3 | AAAI | [{"id": null, "name": "Alessandro Cimatti", "affiliations": []}, {"id": null, "name": "Andrea Micheli", "affiliations": []}, {"id": null, "name": "Marco Roveri", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Temporal planning is an active research area of Artificial Intelligence because of its many applications ranging from roboticsto logistics and beyond. Traditionally, authors focused on theautomatic synthesis of plans given a formal representation of thedomain and of the problem. However, the effectiveness of suchtechni... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11018", "DOI": "10.1609/aaai.v31i1.11018"} | ["Computer Science"] |
official:AAAI:028424cda0683724eb097470 | 10.1609/aaai.v31i1.10600 | Multiwinner Approval Rules as Apportionment Methods | 2,017 | null | ["ConferencePaper"] | 6 | AAAI | [{"id": null, "name": "Markus Brill", "affiliations": []}, {"id": null, "name": "Jean-Francois Laslier", "affiliations": []}, {"id": null, "name": "Piotr Skowron", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We establish a link between multiwinner elections and apportionment problems by showing how approval-based multiwinner election rules can be interpreted as methods of apportionment. We consider several multi-winner rules and observe that some, but not all, of them induce apportionment methods that are well established ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10600", "DOI": "10.1609/aaai.v31i1.10600"} | ["Computer Science"] |
official:AAAI:0e8250f519d2fe382a56ec8a | 10.1609/aaai.v31i1.10534 | Arnold: An Autonomous Agent to Play FPS Games | 2,017 | null | ["ConferencePaper"] | 5 | AAAI | [{"id": null, "name": "Devendra Singh Chaplot", "affiliations": []}, {"id": null, "name": "Guillaume Lample", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Advances in deep reinforcement learning have allowed autonomous agents to perform well on Atari games, often outperforming humans, using only raw pixels to make their decisions. However, most of these games take place in 2D environments that are fully observable to the agent. In this paper, we present Arnold, a complet... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10534", "DOI": "10.1609/aaai.v31i1.10534"} | ["Computer Science"] |
official:AAAI:7fa656e80d106728b7eb9419 | 10.1609/aaai.v31i1.10675 | On the Transitivity of Hypernym-Hyponym Relations in Data-Driven Lexical Taxonomies | 2,017 | null | ["ConferencePaper"] | 8 | AAAI | [{"id": null, "name": "Jiaqing Liang", "affiliations": []}, {"id": null, "name": "Yi Zhang", "affiliations": []}, {"id": null, "name": "Yanghua Xiao", "affiliations": []}, {"id": null, "name": "Haixun Wang", "affiliations": []}, {"id": null, "name": "Wei Wang", "affiliations": []}, {"id": null, "name": "Pinpin Zhu", "a... | null | [] | Computer Science | null | null | false | null | Taxonomy is indispensable in understanding natural language. A variety of large scale, usage-based, data-driven lexical taxonomies have been constructed in recent years.Hypernym-hyponym relationship, which is considered as the backbone of lexical taxonomies can not only be used to categorize the data but also enables g... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10675", "DOI": "10.1609/aaai.v31i1.10675"} | ["Computer Science"] |
official:AAAI:9976ac6014c5944f60a129fb | 10.1609/aaai.v31i1.10898 | Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption | 2,017 | null | ["ConferencePaper"] | 10 | AAAI | [{"id": null, "name": "Tameem Adel", "affiliations": []}, {"id": null, "name": "Han Zhao", "affiliations": []}, {"id": null, "name": "Alexander Wong", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Domain adaptation addresses learning tasks where training is performed on data from one domain whereas testing is performed on data belonging to a different but related domain. Assumptions about the relationship between the source and target domains should lead to tractable solutions on the one hand, and be realistic o... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10898", "DOI": "10.1609/aaai.v31i1.10898"} | ["Computer Science"] |
official:AAAI:8366bcc2cd84e37c55b8e77e | 10.1609/aaai.v31i1.11006 | Attentive Interactive Neural Networks for Answer Selection in Community Question Answering | 2,017 | null | ["ConferencePaper"] | 29 | AAAI | [{"id": null, "name": "Xiaodong Zhang", "affiliations": []}, {"id": null, "name": "Sujian Li", "affiliations": []}, {"id": null, "name": "Lei Sha", "affiliations": []}, {"id": null, "name": "Houfeng Wang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Answer selection plays a key role in community question answering (CQA). Previous research on answer selection usually ignores the problems of redundancy and noise prevalent in CQA. In this paper, we propose to treat different text segments differently and design a novel attentive interactive neural network (AI-NN) to ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11006", "DOI": "10.1609/aaai.v31i1.11006"} | ["Computer Science"] |
official:AAAI:e676c773a21546da3db14c87 | 10.1609/aaai.v31i1.10749 | Beyond Monte Carlo Tree Search: Playing Go with Deep Alternative Neural Network and Long-Term Evaluation | 2,017 | null | ["ConferencePaper"] | 3 | AAAI | [{"id": null, "name": "Jinzhuo Wang", "affiliations": []}, {"id": null, "name": "Wenmin Wang", "affiliations": []}, {"id": null, "name": "Ronggang Wang", "affiliations": []}, {"id": null, "name": "Wen Gao", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Monte Carlo tree search (MCTS) is extremely popular in computer Go which determines each action by enormous simulations in a broad and deep search tree. However, human experts select most actions by pattern analysis and careful evaluation rather than brute search of millions of future interactions. In this paper, we pr... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10749", "DOI": "10.1609/aaai.v31i1.10749"} | ["Computer Science"] |
official:AAAI:b17853030925ccd23035a51c | 10.1609/aaai.v31i1.10493 | Multi-Task Deep Learning for User Intention Understanding in Speech Interaction Systems | 2,017 | null | ["ConferencePaper"] | 6 | AAAI | [{"id": null, "name": "Yishuang Ning", "affiliations": []}, {"id": null, "name": "Jia Jia", "affiliations": []}, {"id": null, "name": "Zhiyong Wu", "affiliations": []}, {"id": null, "name": "Runnan Li", "affiliations": []}, {"id": null, "name": "Yongsheng An", "affiliations": []}, {"id": null, "name": "Yanfeng Wang", "... | null | [] | Computer Science | null | null | false | null | Speech interaction systems have been gaining popularity in recent years. The main purpose of these systems is to generate more satisfactory responses according to users' speech utterances, in which the most critical problem is to analyze user intention. Researches show that user intention conveyed through speech is not... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10493", "DOI": "10.1609/aaai.v31i1.10493"} | ["Computer Science"] |
official:AAAI:6e36f0d78b6bdb680bf5d0f5 | 10.1609/aaai.v31i1.10852 | Compressed K-Means for Large-Scale Clustering | 2,017 | null | ["ConferencePaper"] | 37 | AAAI | [{"id": null, "name": "Xiaobo Shen", "affiliations": []}, {"id": null, "name": "Weiwei Liu", "affiliations": []}, {"id": null, "name": "Ivor Tsang", "affiliations": []}, {"id": null, "name": "Fumin Shen", "affiliations": []}, {"id": null, "name": "Quan-Sen Sun", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Large-scale clustering has been widely used in many applications, and has received much attention. Most existing clustering methods suffer from both expensive computation and memory costs when applied to large-scale datasets. In this paper, we propose a novel clustering method, dubbed compressed k-means (CKM), for fast... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10852", "DOI": "10.1609/aaai.v31i1.10852"} | ["Computer Science"] |
official:AAAI:e8937cf3c8f0a461cd104e84 | 10.1609/aaai.v31i1.11138 | null | 2,017 | 2017-02-12 | ["ConferencePaper"] | 14 | AAAI | [{"id": null, "name": "Daniel Fremont", "affiliations": []}, {"id": null, "name": "Markus Rabe", "affiliations": []}, {"id": null, "name": "Sanjit Seshia", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We introduce the problem Max#SAT, an extension of model counting (#SAT). Given a formula over sets of variables X, Y, and Z, the Max#SAT problem is to maximize over the variables X the number of assignments to Y that can be extended to a solution with some assignment to Z. We demonstrate that Max#SAT has applications i... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11138", "DOI": "10.1609/aaai.v31i1.11138", "S2": "ae4b984f2f36ee0849b5903fda0e0bfd89d01486", "OpenAlex": "W2605327361"} | ["Computer Science"] |
official:AAAI:100047650e7e12f221e0eab1 | 10.1609/aaai.v31i1.10717 | Adverse Drug Reaction Prediction with Symbolic Latent Dirichlet Allocation | 2,017 | null | ["ConferencePaper"] | 21 | AAAI | [{"id": null, "name": "Cao Xiao", "affiliations": []}, {"id": null, "name": "Ping Zhang", "affiliations": []}, {"id": null, "name": "W. Chaovalitwongse", "affiliations": []}, {"id": null, "name": "Jianying Hu", "affiliations": []}, {"id": null, "name": "Fei Wang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Adverse drug reaction (ADR) is a major burden for patients and healthcare industry. It usually causes preventable hospitalizations and deaths, while associated with a huge amount of cost. Traditional preclinical in vitro safety profiling and clinical safety trials are restricted in terms of small scale, long duration, ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10717", "DOI": "10.1609/aaai.v31i1.10717"} | ["Computer Science"] |
official:AAAI:893cc39db460c8862f023845 | 10.1609/aaai.v31i1.10968 | Lattice-Based Recurrent Neural Network Encoders for Neural Machine Translation | 2,017 | null | ["ConferencePaper"] | 23 | AAAI | [{"id": null, "name": "Jinsong Su", "affiliations": []}, {"id": null, "name": "Zhixing Tan", "affiliations": []}, {"id": null, "name": "Deyi Xiong", "affiliations": []}, {"id": null, "name": "Rongrong Ji", "affiliations": []}, {"id": null, "name": "Xiaodong Shi", "affiliations": []}, {"id": null, "name": "Yang Liu", "a... | null | [] | Computer Science | null | null | false | null | Neural machine translation (NMT) heavily relies on word-level modelling to learn semantic representations of input sentences.However, for languages without natural word delimiters (e.g., Chinese) where input sentences have to be tokenized first,conventional NMT is confronted with two issues:1) it is difficult to find a... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10968", "DOI": "10.1609/aaai.v31i1.10968"} | ["Computer Science"] |
official:AAAI:b2de95d2acf191d9f153c5b1 | 10.1609/aaai.v31i1.10501 | Visual Sentiment Analysis by Attending on Local Image Regions | 2,017 | null | ["ConferencePaper"] | 115 | AAAI | [{"id": null, "name": "Quanzeng You", "affiliations": []}, {"id": null, "name": "Hailin Jin", "affiliations": []}, {"id": null, "name": "Jiebo Luo", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Visual sentiment analysis, which studies the emotional response of humans on visual stimuli such as images and videos, has been an interesting and challenging problem. It tries to understand the high-level content of visual data. The success of current models can be attributed to the development of robust algorithms fr... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10501", "DOI": "10.1609/aaai.v31i1.10501"} | ["Computer Science"] |
official:AAAI:d58d30af068263807b9b9ce8 | 10.1609/aaai.v31i1.11088 | High-Resolution Mobile Fingerprint Matching via Deep Joint KNN-Triplet Embedding | 2,017 | null | ["ConferencePaper"] | 10 | AAAI | [{"id": null, "name": "Fandong Zhang", "affiliations": []}, {"id": null, "name": "Jufu Feng", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In mobile devices, the limited area of fingerprint sensors brings demand of partial fingerprint matching. Existing fingerprint authentication algorithms are mainly based on minutiae matching. However, their accuracy degrades significantly for partial-to-partial matching due to the lack of minutiae. Optical fingerprint ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11088", "DOI": "10.1609/aaai.v31i1.11088"} | ["Computer Science"] |
official:AAAI:b49de8079eedcd807ec90bee | 10.1609/aaai.v31i1.11130 | null | 2,017 | 2017-02-12 | ["ConferencePaper"] | 5 | AAAI | [{"id": null, "name": "Guillaume Perez", "affiliations": []}, {"id": null, "name": "Jean-Charles Régin", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Recent developments of efficient propagators, operations and creation methods for MDDs allow us to directly build efficient MDD-based models, without the need for intermediate data structures. In this paper, we take another step in this direction by improving the propagators of cost MDDs. In addition, we introduce a so... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11130", "DOI": "10.1609/aaai.v31i1.11130", "S2": "64098cd495566241637b483ace535c0c9941b2e7", "OpenAlex": "W2604871776"} | ["Computer Science"] |
official:AAAI:2966de40bbc9116069ad4774 | 10.1609/aaai.v31i1.11043 | Latent Dirichlet Allocation for Unsupervised Activity Analysis on an Autonomous Mobile Robot | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Paul Duckworth", "affiliations": []}, {"id": null, "name": "Muhannad Alomari", "affiliations": []}, {"id": null, "name": "James Charles", "affiliations": []}, {"id": null, "name": "David Hogg", "affiliations": []}, {"id": null, "name": "Anthony Cohn", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | For autonomous robots to collaborate on joint tasks with humans they require a shared understanding of an observed scene. We present a method for unsupervised learning of common human movements and activities on an autonomous mobile robot, which generalises and improves on recent results. Our framework encodes multiple... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11043", "DOI": "10.1609/aaai.v31i1.11043"} | ["Computer Science"] |
official:AAAI:d6b9f08347b0718b476fe6c5 | 10.1609/aaai.v31i1.10527 | An Evolutionary Algorithm Based Framework for Task Allocation in Multi-Robot Teams | 2,017 | null | ["ConferencePaper"] | 3 | AAAI | [{"id": null, "name": "Muhammad Arif", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Multi-Robot Task Allocation (MRTA) has no formal framework which could provide solutions covering different domains within the MRTA taxonomy without changing the optimization scheme. This research aims to develop a novel framework using evolutionary computing. The study proposes a modular approach towards developing th... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10527", "DOI": "10.1609/aaai.v31i1.10527"} | ["Computer Science"] |
official:AAAI:5c296f450923b51fe4abfbfe | 10.1609/aaai.v31i1.10766 | Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU | 2,017 | null | ["ConferencePaper"] | 4 | AAAI | [{"id": null, "name": "Nozomi Nori", "affiliations": []}, {"id": null, "name": "Hisashi Kashima", "affiliations": []}, {"id": null, "name": "Kazuto Yamashita", "affiliations": []}, {"id": null, "name": "Susumu Kunisawa", "affiliations": []}, {"id": null, "name": "Yuichi Imanaka", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Accurate assessment of the severity of a patient's condition plays a fundamental role in acute hospital care such as that provided in an intensive care unit (ICU). ICU clinicians are required to make sense of a large amount of clinical data in a limited time to estimate the severity of a patient's condition, which ulti... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10766", "DOI": "10.1609/aaai.v31i1.10766"} | ["Computer Science"] |
official:AAAI:ae701b91ff03ec7531ae905c | 10.1609/aaai.v31i1.10662 | Dancing with Decision Diagrams: A Combined Approach to Exact Cover | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Masaaki Nishino", "affiliations": []}, {"id": null, "name": "Norihito Yasuda", "affiliations": []}, {"id": null, "name": "Shin-ichi Minato", "affiliations": []}, {"id": null, "name": "Masaaki Nagata", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Exact cover is the problem of finding subfamilies, S*, of a family of sets, S, over universe U, where S* forms a partition of U. It is a popular NP-hard problem appearing in a wide range of computer science studies. Knuth's algorithm DLX, a backtracking-based depth-first search implemented with the data structure calle... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10662", "DOI": "10.1609/aaai.v31i1.10662"} | ["Computer Science"] |
official:AAAI:01d4329d7323b2aef4623f00 | 10.1609/aaai.v31i1.11096 | Rethinking the Link Prediction Problem in Signed Social Networks | 2,017 | null | ["ConferencePaper"] | 11 | AAAI | [{"id": null, "name": "Xiaoming Li", "affiliations": []}, {"id": null, "name": "Hui Fang", "affiliations": []}, {"id": null, "name": "Jie Zhang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We rethink the link prediction problem in signed social networks by also considering "no-relation" as a future status of a node pair, rather than simply distinguishing positive and negative links proposed in the literature. To understand the underlying mechanism of link formation in signed networks, we propose a featur... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11096", "DOI": "10.1609/aaai.v31i1.11096"} | ["Computer Science"] |
official:AAAI:fe285a37e3230389ce5b1178 | 10.1609/aaai.v31i1.10998 | Representations of Context in Recognizing the Figurative and Literal Usages of Idioms | 2,017 | null | ["ConferencePaper"] | 7 | AAAI | [{"id": null, "name": "Changsheng Liu", "affiliations": []}, {"id": null, "name": "Rebecca Hwa", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Many idiomatic expressions can be interpreted literally or figuratively, depending on the context in which they occur. Developing an appropriate computational model of the context is crucial for automatic idiom usage recognition. While many existing methods incorporate some elements of context, they have not sufficient... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10998", "DOI": "10.1609/aaai.v31i1.10998"} | ["Computer Science"] |
official:AAAI:336ce3ed898601f4881c99d0 | 10.1609/aaai.v31i1.10492 | A Declarative Approach to Data-Driven Fact Checking | 2,017 | null | ["ConferencePaper"] | 4 | AAAI | [{"id": null, "name": "Julien Leblay", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Fact checking is an essential part of any investigative work. For linguistic, psychological and social reasons, it is an inherently human task. Yet, modern media make it increasingly difficult for experts to keep up with the pace at which information is produced. Hence, we believe there is value in tools to assist them... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10492", "DOI": "10.1609/aaai.v31i1.10492"} | ["Computer Science"] |
official:AAAI:8b2d43d0ed973a468db3c985 | 10.1609/aaai.v31i1.10892 | Heavy-Tailed Analogues of the Covariance Matrix for ICA | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Joseph Anderson", "affiliations": []}, {"id": null, "name": "Navin Goyal", "affiliations": []}, {"id": null, "name": "Anupama Nandi", "affiliations": []}, {"id": null, "name": "Luis Rademacher", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Independent Component Analysis (ICA) is the problem of learning a square matrix A, given samples of X = AS, where S is a random vector with independent coordinates. Most existing algorithms are provably efficient only when each Si has finite and moderately valued fourth moment. However, there are practical applications... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10892", "DOI": "10.1609/aaai.v31i1.10892"} | ["Computer Science"] |
official:AAAI:25743be05dd0384cfc334b68 | 10.1609/aaai.v31i1.10834 | Generalized Ambiguity Decompositions for Classification with Applications in Active Learning and Unsupervised Ensemble Pruning | 2,017 | null | ["ConferencePaper"] | 10 | AAAI | [{"id": null, "name": "Zhengshen Jiang", "affiliations": []}, {"id": null, "name": "Hongzhi Liu", "affiliations": []}, {"id": null, "name": "Bin Fu", "affiliations": []}, {"id": null, "name": "Zhonghai Wu", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Error decomposition analysis is a key problem for ensemble learning. Two commonly used error decomposition schemes, the classic Ambiguity Decomposition and Bias-Variance-Covariance decomposition, are only suitable for regression tasks with square loss. We generalized the classic Ambiguity Decomposition from regression ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10834", "DOI": "10.1609/aaai.v31i1.10834"} | ["Computer Science"] |
official:AAAI:e00a25fbceb77555cfef2934 | 10.1609/aaai.v31i1.10506 | Local Discriminant Hyperalignment for Multi-Subject fMRI Data Alignment | 2,017 | null | ["ConferencePaper"] | 4 | AAAI | [{"id": null, "name": "Muhammad Yousefnezhad", "affiliations": []}, {"id": null, "name": "Daoqiang Zhang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Multivariate Pattern (MVP) classification can map different cognitive states to the brain tasks. One of the main challenges in MVP analysis is validating the generated results across subjects. However, analyzing multi-subject fMRI data requires accurate functional alignments between neuronal activities of different sub... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10506", "DOI": "10.1609/aaai.v31i1.10506"} | ["Computer Science"] |
official:AAAI:fadad5e3d763c2f659869add | 10.1609/aaai.v31i1.10809 | Self-Paced Learning: An Implicit Regularization Perspective | 2,017 | null | ["ConferencePaper"] | 25 | AAAI | [{"id": null, "name": "Yanbo Fan", "affiliations": []}, {"id": null, "name": "Ran He", "affiliations": []}, {"id": null, "name": "Jian Liang", "affiliations": []}, {"id": null, "name": "Baogang Hu", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Self-paced learning (SPL) mimics the cognitive mechanism of humans and animals that gradually learns from easy to hard samples. One key issue in SPL is to obtain better weighting strategy that is determined by the minimizer function. Existing methods usually pursue this by artificially designing the explicit form of SP... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10809", "DOI": "10.1609/aaai.v31i1.10809"} | ["Computer Science"] |
official:AAAI:11639aa792186f0d09ec017d | 10.1609/aaai.v31i1.11162 | Inductive Reasoning about Ontologies Using Conceptual Spaces | 2,017 | null | ["ConferencePaper"] | 5 | AAAI | [{"id": null, "name": "Zied Bouraoui", "affiliations": []}, {"id": null, "name": "Shoaib Jameel", "affiliations": []}, {"id": null, "name": "Steven Schockaert", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Structured knowledge about concepts plays an increasingly important role in areas such as information retrieval. The available ontologies and knowledge graphs that encode such conceptual knowledge, however, are inevitably incomplete. This observation has led to a number of methods that aim to automatically complete exi... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11162", "DOI": "10.1609/aaai.v31i1.11162"} | ["Computer Science"] |
official:AAAI:455caba28270b0cdc59b4897 | 10.1609/aaai.v31i1.10619 | Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices | 2,017 | null | ["ConferencePaper"] | 17 | AAAI | [{"id": null, "name": "Yang Liu", "affiliations": []}, {"id": null, "name": "Yiling Chen", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Peer prediction mechanisms are often adopted to elicit truthful contributions from crowd workers when no ground-truth verification is available. Recently, mechanisms of this type have been developed to incentivize effort exertion, in addition to truthful elicitation. In this paper, we study a sequential peer prediction... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10619", "DOI": "10.1609/aaai.v31i1.10619"} | ["Computer Science"] |
official:AAAI:67ac827c0e38adc5026f7ef8 | 10.1609/aaai.v31i1.10641 | SAT Competition 2016: Recent Developments | 2,017 | null | ["ConferencePaper"] | 37 | AAAI | [{"id": null, "name": "Tomas Balyo", "affiliations": []}, {"id": null, "name": "Marijn Heule", "affiliations": []}, {"id": null, "name": "Matti Jarvisalo", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We give an overview of SAT Competition 2016, the 2016 edition of thefamous competition for Boolean satisfiability (SAT) solvers with over 20 years of history. A key aim is to point out ``what's hot'' in SAT competitions in 2016, i.e., new developments in thecompetition series, including new competition tracks and new s... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10641", "DOI": "10.1609/aaai.v31i1.10641"} | ["Computer Science"] |
official:AAAI:0efd0a760ca1b336f857cd2a | 10.1609/aaai.v31i1.10483 | Correlated Cascades: Compete or Cooperate | 2,017 | null | ["ConferencePaper"] | 21 | AAAI | [{"id": null, "name": "Ali Zarezade", "affiliations": []}, {"id": null, "name": "Ali Khodadadi", "affiliations": []}, {"id": null, "name": "Mehrdad Farajtabar", "affiliations": []}, {"id": null, "name": "Hamid Rabiee", "affiliations": []}, {"id": null, "name": "Hongyuan Zha", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In real world social networks, there are multiple cascades which are rarely independent. They usually compete or cooperate with each other. Motivated by the reinforcement theory in sociology we leverage the fact that adoption of a user to any behavior is modeled by the aggregation of behaviors of its neighbors. We use ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10483", "DOI": "10.1609/aaai.v31i1.10483"} | ["Computer Science"] |
official:AAAI:cfac4392b97bd321bf2bf03a | 10.1609/aaai.v31i1.10936 | Factorization Bandits for Interactive Recommendation | 2,017 | null | ["ConferencePaper"] | 46 | AAAI | [{"id": null, "name": "Huazheng Wang", "affiliations": []}, {"id": null, "name": "Qingyun Wu", "affiliations": []}, {"id": null, "name": "Hongning Wang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We perform online interactive recommendation via a factorization-based bandit algorithm. Low-rank matrix completion is performed over an incrementally constructed user-item preference matrix, where an upper confidence bound based item selection strategy is developed to balance the exploit/explore trade-off during onlin... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10936", "DOI": "10.1609/aaai.v31i1.10936"} | ["Computer Science"] |
official:AAAI:6fef462071ee7364670d2297 | 10.1609/aaai.v31i1.10777 | Denoising Criterion for Variational Auto-Encoding Framework | 2,017 | null | ["ConferencePaper"] | 89 | AAAI | [{"id": null, "name": "Daniel Im Im", "affiliations": []}, {"id": null, "name": "Sungjin Ahn", "affiliations": []}, {"id": null, "name": "Roland Memisevic", "affiliations": []}, {"id": null, "name": "Yoshua Bengio", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Denoising autoencoders (DAE) are trained to reconstruct their clean inputs with noise injected at the input level, while variational autoencoders (VAE) are trained with noise injected in their stochastic hidden layer, with a regularizer that encourages this noise injection. In this paper, we show that injecting noise b... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10777", "DOI": "10.1609/aaai.v31i1.10777"} | ["Computer Science"] |
official:AAAI:fc14ab8549d8d8af7d3d3938 | 10.1609/aaai.v31i1.10913 | When and Why Are Deep Networks Better Than Shallow Ones? | 2,017 | null | ["ConferencePaper"] | 87 | AAAI | [{"id": null, "name": "Hrushikesh Mhaskar", "affiliations": []}, {"id": null, "name": "Qianli Liao", "affiliations": []}, {"id": null, "name": "Tomaso Poggio", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | While the universal approximation property holds both for hierarchical and shallow networks, deep networks can approximate the class of compositional functions as well as shallow networks but with exponentially lower number of training parameters and sample complexity. Compositional functions are obtained as a hierarch... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10913", "DOI": "10.1609/aaai.v31i1.10913"} | ["Computer Science"] |
official:AAAI:f62b8b678f6c55a810cee980 | 10.1609/aaai.v31i1.11122 | The Complexity of Succinct Elections | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Zack Fitzsimmons", "affiliations": []}, {"id": null, "name": "Edith Hemaspaandra", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | The computational study of elections generally assumes that the preferences of the electorate come in as a list of votes. Depending on the context, it may be much more natural to represent the preferences of the electorate succinctly, as the distinct votes and their counts. Though the succinct representation may be exp... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11122", "DOI": "10.1609/aaai.v31i1.11122"} | ["Computer Science"] |
official:AAAI:4efca3594b4e20d5b6fa5019 | 10.1609/aaai.v31i1.10781 | Parametric Dual Maximization for Non-Convex Learning Problems | 2,017 | null | ["ConferencePaper"] | 0 | AAAI | [{"id": null, "name": "Yuxun Zhou", "affiliations": []}, {"id": null, "name": "Zhaoyi Kang", "affiliations": []}, {"id": null, "name": "Costas Spanos", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We consider a class of non-convex learning problems that can be formulated as jointly optimizing regularized hinge loss and a set of auxiliary variables. Such problems encompass but are not limited to various versions of semi-supervised learning,learning with hidden structures, robust learning, etc. Existing methods ei... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10781", "DOI": "10.1609/aaai.v31i1.10781"} | ["Computer Science"] |
official:AAAI:8ac9cfdf047d12eb30736a33 | 10.1609/aaai.v31i1.10922 | Weighted Bandits or: How Bandits Learn Distorted Values That Are Not Expected | 2,017 | null | ["ConferencePaper"] | 0 | AAAI | [{"id": null, "name": "Aditya Gopalan", "affiliations": []}, {"id": null, "name": "Prashanth L. A.", "affiliations": []}, {"id": null, "name": "Michael Fu", "affiliations": []}, {"id": null, "name": "Steve Marcus", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Motivated by models of human decision making proposed to explain commonly observed deviations from conventional expected value preferences, we formulate two stochastic multi-armed bandit problems with distorted probabilities on the cost distributions: the classic K-armed bandit and the linearly parameterized bandit. In... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10922", "DOI": "10.1609/aaai.v31i1.10922"} | ["Computer Science"] |
official:AAAI:ab703d545e8f5854e096bbb4 | 10.1609/aaai.v31i1.10899 | Continuous Conditional Dependency Network for Structured Regression | 2,017 | null | ["ConferencePaper"] | 0 | AAAI | [{"id": null, "name": "Chao Han", "affiliations": []}, {"id": null, "name": "Mohamed Ghalwash", "affiliations": []}, {"id": null, "name": "Zoran Obradovic", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Structured regression on graphs aims to predict response variables from multiple nodes by discovering and exploiting the dependency structure among response variables. This problem is challenging since dependencies among response variables are always unknown, and the associated prior knowledge is non-symmetric. In prev... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10899", "DOI": "10.1609/aaai.v31i1.10899"} | ["Computer Science"] |
official:AAAI:18e9b7c87782b5a0db247081 | 10.1609/aaai.v31i1.10585 | Optimizing Positional Scoring Rules for Rank Aggregation | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Ioannis Caragiannis", "affiliations": []}, {"id": null, "name": "Xenophon Chatzigeorgiou", "affiliations": []}, {"id": null, "name": "George Krimpas", "affiliations": []}, {"id": null, "name": "Alexandros Voudouris", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Nowadays, several crowdsourcing projects exploit social choice methods for computing an aggregate ranking of alternatives given individual rankings provided by workers. Motivated by such systems, we consider a setting where each worker is asked to rank a fixed (small) number of alternatives and, then, a positional scor... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10585", "DOI": "10.1609/aaai.v31i1.10585"} | ["Computer Science"] |
official:AAAI:b7f88b6adad96fa5035e48aa | 10.1609/aaai.v31i1.11063 | null | 2,017 | 2017-02-12 | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Min Yang", "affiliations": []}, {"id": null, "name": "Ziyu Lu", "affiliations": []}, {"id": null, "name": "Xiaojun Chen", "affiliations": []}, {"id": null, "name": "Fei Xu", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | With an increasing number of paid writers posting fake reviews to promote or demote some target entities through Internet, review spammer detection has become a crucial and challenging task. In this paper, we propose a three-phase method to address the problem of identifying review spammer groups and individual spammer... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11063", "DOI": "10.1609/aaai.v31i1.11063", "S2": "5ee8768ea32b32c8840c9951bef410f656dbb07b", "OpenAlex": "W2604654764"} | ["Computer Science"] |
official:AAAI:62e8732080aa493efc208fa8 | 10.1609/aaai.v31i1.10792 | null | 2,017 | 2017-02-13 | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Li Wang", "affiliations": []}, {"id": null, "name": "Qi Mao", "affiliations": []}, {"id": null, "name": "Ivor Tsang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Learning a smooth skeleton in a low-dimensional space from noisy data becomes important in computer vision and computational biology. Existing methods assume that the manifold constructed from the data is smooth, but they lack the ability to model skeleton structures from noisy data. To overcome this issue, we propose ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10792", "DOI": "10.1609/aaai.v31i1.10792", "S2": "717b98a857b912206de467dcd6fb23d3294f364b", "OpenAlex": "W2604519158"} | ["Computer Science"] |
official:AAAI:00c6fbdfb3b14eb1b7263210 | 10.1609/aaai.v31i1.10980 | Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge | 2,017 | null | ["ConferencePaper"] | 3 | AAAI | [{"id": null, "name": "Matt Gardner", "affiliations": []}, {"id": null, "name": "Jayant Krishnamurthy", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Traditional semantic parsers map language onto compositional, executable queries in a fixed schema. This mapping allows them to effectively leverage the information contained in large, formal knowledge bases (KBs, e.g., Freebase) to answer questions, but it is also fundamentally limiting---these semantic parsers can on... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10980", "DOI": "10.1609/aaai.v31i1.10980"} | ["Computer Science"] |
official:AAAI:1039923d50b6cbcf38baaa0d | 10.1609/aaai.v31i1.11095 | Redesigning Stochastic Environments for Maximized Utility | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Sarah Keren", "affiliations": []}, {"id": null, "name": "Avigdor Gal", "affiliations": []}, {"id": null, "name": "Erez Karpas", "affiliations": []}, {"id": null, "name": "Luis Pineda", "affiliations": []}, {"id": null, "name": "Shlomo Zilberstein", "affiliations": []}] | null | [] | Computer Science | null | null | true | null | We present the Utility Maximizing Design (UMD) model for optimally redesigning stochastic environments to achieve maximized performance. This model suits well contemporary applications that involve the design of environments where robots and humans co-exist an co-operate, e.g., vacuum cleaning robot. We discuss two spe... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11095", "DOI": "10.1609/aaai.v31i1.11095"} | ["Computer Science"] |
official:AAAI:1c18021725ca8a3347b0839f | 10.1609/aaai.v31i1.11219 | Closing the Loop for Edge Detection and Object Proposals | 2,017 | null | ["ConferencePaper"] | 4 | AAAI | [{"id": null, "name": "Yao Lu", "affiliations": []}, {"id": null, "name": "Linda Shapiro", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Edge grouping and object perception are unified procedures in perceptual organization. However the computer vision literature classifies them as independent tasks. In this paper, we argue that edge detection and object proposals should benefit one another. To achieve this, we go beyond bounding boxes and extract closed... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11219", "DOI": "10.1609/aaai.v31i1.11219"} | ["Computer Science"] |
official:AAAI:4a5d04553a728e96633dfb82 | 10.1609/aaai.v31i1.10826 | null | 2,017 | 2017-02-13 | ["ConferencePaper"] | 118 | AAAI | [{"id": null, "name": "Ben Tan", "affiliations": []}, {"id": null, "name": "Yu Zhang", "affiliations": []}, {"id": null, "name": "Sinno Pan", "affiliations": []}, {"id": null, "name": "Qiang Yang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In this paper, we study a novel transfer learning problem termed Distant Domain Transfer Learning (DDTL). Different from existing transfer learning problems which assume that there is a close relation between the source domain and the target domain, in the DDTL problem, the target domain can be totally different from t... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10826", "DOI": "10.1609/aaai.v31i1.10826", "S2": "3af110e8b1e687275f6edf7eaecc0d28cfafa88e", "OpenAlex": "W4293659930"} | ["Computer Science"] |
official:AAAI:c2b9b1124f9359b8a4112913 | 10.1609/aaai.v31i1.11171 | Extracting Urban Microclimates from Electricity Bills | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Thuy Vu", "affiliations": []}, {"id": null, "name": "D. Stott Parker", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Sustainable energy policies are of growing importance in all urban centers.Climate - and climate change - will play increasingly important roles in these policies.Climate zones defined by the California Energy Commissionhave long been influential in energy management.For example, recently a two-zone division of Los Ang... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11171", "DOI": "10.1609/aaai.v31i1.11171"} | ["Computer Science"] |
official:AAAI:7c03235fce7771545bc9b2f0 | 10.1609/aaai.v31i1.11211 | Deep Correlated Metric Learning for Sketch-based 3D Shape Retrieval | 2,017 | null | ["ConferencePaper"] | 37 | AAAI | [{"id": null, "name": "Guoxian Dai", "affiliations": []}, {"id": null, "name": "Jin Xie", "affiliations": []}, {"id": null, "name": "Fan Zhu", "affiliations": []}, {"id": null, "name": "Yi Fang", "affiliations": []}] | null | [] | Computer Science | null | null | true | null | The explosive growth of 3D models has led to the pressing demand for an efficient searching system. Traditional model-based search is usually not convenient, since people don't always have 3D model available by side. The sketch-based 3D shape retrieval is a promising candidate due to its simpleness and efficiency. The ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11211", "DOI": "10.1609/aaai.v31i1.11211"} | ["Computer Science"] |
official:AAAI:712295567bbfe36500a2b4b7 | 10.1609/aaai.v31i1.11116 | null | 2,017 | 2017-02-12 | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Luigi Asprino", "affiliations": []}, {"id": null, "name": "Valentina Presutti", "affiliations": []}, {"id": null, "name": "Aldo Gangemi", "affiliations": []}, {"id": null, "name": "Paolo Ciancarini", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | The need of handling semantic heterogeneity of resources is a key problem of the Semantic Web. State of the art techniques for ontology matching are the key technology for addressing this issue. However, they only partially exploit the natural lan- guage descriptions of ontology entities and they are mostly unable to f... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11116", "DOI": "10.1609/aaai.v31i1.11116", "S2": "b62c05ede9564faa3e68fe527ac81c644bb1224d", "OpenAlex": "W2604748909"} | ["Computer Science"] |
official:AAAI:56e7a04aa3d279516213ed6b | 10.1609/aaai.v31i1.10944 | Local Centroids Structured Non-Negative Matrix Factorization | 2,017 | null | ["ConferencePaper"] | 16 | AAAI | [{"id": null, "name": "Hongchang Gao", "affiliations": []}, {"id": null, "name": "Feiping Nie", "affiliations": []}, {"id": null, "name": "Heng Huang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Non-negative Matrix Factorization (NMF) has attracted much attention and been widely used in real-world applications. As a clustering method, it fails to handle the case where data points lie in a complicated geometry structure. Existing methods adopt single global centroid for each cluster, failing to capture the mani... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10944", "DOI": "10.1609/aaai.v31i1.10944"} | ["Computer Science"] |
official:AAAI:7778fa3022f88f14b4c64bca | 10.1609/aaai.v31i1.10756 | ESPACE: Accelerating Convolutional Neural Networks via Eliminating Spatial and Channel Redundancy | 2,017 | null | ["ConferencePaper"] | 11 | AAAI | [{"id": null, "name": "Shaohui Lin", "affiliations": []}, {"id": null, "name": "Rongrong Ji", "affiliations": []}, {"id": null, "name": "Chao Chen", "affiliations": []}, {"id": null, "name": "Feiyue Huang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Recent years have witnessed an extensive popularity of convolutional neural networks (CNNs) in various computer vision and artificial intelligence applications. However, the performance gains have come at a cost of substantially intensive computation complexity, which prohibits its usage inresource-limited applications... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10756", "DOI": "10.1609/aaai.v31i1.10756"} | ["Computer Science"] |
official:AAAI:aaf91161b99a507d0b65d2b0 | 10.1609/aaai.v31i1.11181 | Healthy Cognitive Aging: A Hybrid Random Vector Functional-Link Model for the Analysis of Alzheimer's Disease | 2,017 | null | ["ConferencePaper"] | 15 | AAAI | [{"id": null, "name": "Peng Dai", "affiliations": []}, {"id": null, "name": "Femida Gwadry-Sridhar", "affiliations": []}, {"id": null, "name": "Michael Bauer", "affiliations": []}, {"id": null, "name": "Michael Borrie", "affiliations": []}, {"id": null, "name": "Xue Teng", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Alzheimer's disease (AD) is a genetically complex neurodegenerative disease, which leads to irreversible brain damage, severe cognitive problems and ultimately death. A number of clinical trials and study initiatives have been set up to investigate AD pathology, leading to large amounts of high dimensional heterogeneou... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11181", "DOI": "10.1609/aaai.v31i1.11181"} | ["Computer Science"] |
official:AAAI:83214741f9ba6f0eea6122b5 | 10.1609/aaai.v31i2.19090 | ParkUs: A Novel Vehicle Parking Detection System | 2,017 | null | ["ConferencePaper"] | 9 | AAAI | [{"id": null, "name": "Pietro Carnelli", "affiliations": []}, {"id": null, "name": "Joy Yeh", "affiliations": []}, {"id": null, "name": "Mahesh Sooriyabandara", "affiliations": []}, {"id": null, "name": "Aftab Khan", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Finding on-street parking in congested urban areas is a challenging chore that most drivers worldwide dislike. Previous vehicle traffic studies have estimated that around thirty percent of vehicles travelling in inner city areas are made up of drivers searching for a vacant parking space. While there are hardware senso... | C | {"URL": "https://doi.org/10.1609/aaai.v31i2.19090", "DOI": "10.1609/aaai.v31i2.19090"} | ["Computer Science"] |
official:AAAI:5d8a791a212327ac63a46e08 | 10.1609/aaai.v31i1.10668 | Automated Data Extraction Using Predictive Program Synthesis | 2,017 | null | ["ConferencePaper"] | 22 | AAAI | [{"id": null, "name": "Mohammad Raza", "affiliations": []}, {"id": null, "name": "Sumit Gulwani", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In recent years there has been rising interest in the use of programming-by-example techniques to assist users in data manipulation tasks. Such techniques rely on an explicit input-output examples specification from the user to automatically synthesize programs. However, in a wide range of data extraction tasks it is e... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10668", "DOI": "10.1609/aaai.v31i1.10668"} | ["Computer Science"] |
official:AAAI:7cd30e41fd724116fbffce0c | 10.1609/aaai.v31i1.10480 | Treatment Effect Estimation with Data-Driven Variable Decomposition | 2,017 | null | ["ConferencePaper"] | 28 | AAAI | [{"id": null, "name": "Kun Kuang", "affiliations": []}, {"id": null, "name": "Peng Cui", "affiliations": []}, {"id": null, "name": "Bo Li", "affiliations": []}, {"id": null, "name": "Meng Jiang", "affiliations": []}, {"id": null, "name": "Shiqiang Yang", "affiliations": []}, {"id": null, "name": "Fei Wang", "affiliatio... | null | [] | Computer Science | null | null | false | null | One fundamental problem in causal inference is the treatment effect estimation in observational studies when variables are confounded. Control for confounding effect is generally handled by propensity score. But it treats all observed variables as confounders and ignores the adjustment variables, which have no influenc... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10480", "DOI": "10.1609/aaai.v31i1.10480"} | ["Computer Science"] |
official:AAAI:1633f9845321f06f70805fc3 | 10.1609/aaai.v31i1.11206 | Face Hallucination with Tiny Unaligned Images by Transformative Discriminative Neural Networks | 2,017 | null | ["ConferencePaper"] | 48 | AAAI | [{"id": null, "name": "Xin Yu", "affiliations": []}, {"id": null, "name": "Fatih Porikli", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Conventional face hallucination methods rely heavily on accurate alignment of low-resolution (LR) faces before upsampling them. Misalignment often leads to deficient results and unnatural artifacts for large upscaling factors. However, due to the diverse range of poses and different facial expressions, aligning an LR i... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11206", "DOI": "10.1609/aaai.v31i1.11206"} | ["Computer Science"] |
official:AAAI:4ed3058928d82c9d2ab0a02b | 10.1609/aaai.v31i1.10803 | Efficient Online Model Adaptation by Incremental Simplex Tableau | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Zhixian Lei", "affiliations": []}, {"id": null, "name": "Xuehan Ye", "affiliations": []}, {"id": null, "name": "Yongcai Wang", "affiliations": []}, {"id": null, "name": "Deying Li", "affiliations": []}, {"id": null, "name": "Jia Xu", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Online multi-kernel learning is promising in the era of mobile computing, in which a combined classifier with multiple kernels are offline trained, and online adapts to personalized features for serving the end user precisely and smartly. The online adaptation is mainly carried out at the end-devices, which requires th... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10803", "DOI": "10.1609/aaai.v31i1.10803"} | ["Computer Science"] |
official:AAAI:d36099465c3f7d15f61c3761 | 10.1609/aaai.v31i1.10958 | SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents | 2,017 | null | ["ConferencePaper"] | 506 | AAAI | [{"id": null, "name": "Ramesh Nallapati", "affiliations": []}, {"id": null, "name": "Feifei Zhai", "affiliations": []}, {"id": null, "name": "Bowen Zhou", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model for extractive summarization of documents and show that it achieves performance better than or comparable to state-of-the-art. Our model has the additional advantage of being very interpretable, since it allows visualization of its prediction... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10958", "DOI": "10.1609/aaai.v31i1.10958"} | ["Computer Science"] |
official:AAAI:7351967f6ee420aa7098b604 | 10.1609/aaai.v31i1.10698 | Causal Discovery Using Regression-Based Conditional Independence Tests | 2,017 | null | ["ConferencePaper"] | 20 | AAAI | [{"id": null, "name": "Hao Zhang", "affiliations": []}, {"id": null, "name": "Shuigeng Zhou", "affiliations": []}, {"id": null, "name": "Kun Zhang", "affiliations": []}, {"id": null, "name": "Jihong Guan", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Conditional independence (CI) testing is an important tool in causal discovery. Generally, by using CI tests, a set of Markov equivalence classes w.r.t. the observed data can be estimated by checking whether each pair of variables x and y is d-separated, given a set of variables Z. Due to the curse of dimensionality, C... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10698", "DOI": "10.1609/aaai.v31i1.10698"} | ["Computer Science"] |
official:AAAI:b7be3f1bad845866cde25a0b | 10.1609/aaai.v31i1.10866 | A Riemannian Network for SPD Matrix Learning | 2,017 | null | ["ConferencePaper"] | 258 | AAAI | [{"id": null, "name": "Zhiwu Huang", "affiliations": []}, {"id": null, "name": "Luc Van Gool", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Symmetric Positive Definite (SPD) matrix learning methods have become popular in many image and video processing tasks, thanks to their ability to learn appropriate statistical representations while respecting Riemannian geometry of underlying SPD manifolds. In this paper we build a Riemannian network architecture to o... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10866", "DOI": "10.1609/aaai.v31i1.10866"} | ["Computer Science"] |
official:AAAI:ab6cc58de23806371cd37299 | 10.1609/aaai.v31i1.10960 | A Context-Enriched Neural Network Method for Recognizing Lexical Entailment | 2,017 | null | ["ConferencePaper"] | 9 | AAAI | [{"id": null, "name": "Kun Zhang", "affiliations": []}, {"id": null, "name": "Enhong Chen", "affiliations": []}, {"id": null, "name": "Qi Liu", "affiliations": []}, {"id": null, "name": "Chuanren Liu", "affiliations": []}, {"id": null, "name": "Guangyi Lv", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Recognizing lexical entailment (RLE) always plays an important role in inference of natural language, i.e., identifying whether one word entails another, for example, fox entails animal. In the literature, automatically recognizing lexical entailment for word pairs deeply relies on words' contextual representations. Ho... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10960", "DOI": "10.1609/aaai.v31i1.10960"} | ["Computer Science"] |
official:AAAI:6e5bd4cb340a5c396ff0c4b8 | 10.1609/aaai.v31i1.10694 | Diagnosability Planning for Controllable Discrete Event Systems | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Hassan Ibrahim", "affiliations": []}, {"id": null, "name": "Philippe Dague", "affiliations": []}, {"id": null, "name": "Alban Grastien", "affiliations": []}, {"id": null, "name": "Lina Ye", "affiliations": []}, {"id": null, "name": "Laurent Simon", "affiliations": []}] | null | [] | Computer Science | null | null | true | null | In this paper, we propose an approach to ensure the diagnosability of a partially controllable system. Given a model of correct and faulty behaviors of a partially observable discrete event system, equipped with a set of elementary actions that do not intertwine with autonomous events, we search a diagnosability plan, ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10694", "DOI": "10.1609/aaai.v31i1.10694"} | ["Computer Science"] |
official:AAAI:8a3c5ef7da39764d55155402 | 10.1609/aaai.v31i1.10705 | Nurturing Group-Beneficial Information-Gathering Behaviors Through Above-Threshold Criteria Setting | 2,017 | null | ["ConferencePaper"] | 0 | AAAI | [{"id": null, "name": "Igor Rochlin", "affiliations": []}, {"id": null, "name": "David Sarne", "affiliations": []}, {"id": null, "name": "Maytal Bremer", "affiliations": []}, {"id": null, "name": "Ben Grynhaus", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | This paper studies a criteria-based mechanism for nurturing and enhancing agents' group-benefiting individual efforts whenever the agents are self-interested. The idea is that only those agents that meet the criteria get to benefit from the group effort, giving an incentive to contribute even when it is otherwise indiv... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10705", "DOI": "10.1609/aaai.v31i1.10705"} | ["Computer Science"] |
official:AAAI:84b27441473f6a345ea76e88 | 10.1609/aaai.v31i1.11078 | Semantic Interpretation of Social Network Communities | 2,017 | null | ["ConferencePaper"] | 0 | AAAI | [{"id": null, "name": "Tushar Maheshwari", "affiliations": []}, {"id": null, "name": "Aishwarya Reganti", "affiliations": []}, {"id": null, "name": "Upendra Kumar", "affiliations": []}, {"id": null, "name": "Tanmoy Chakraborty", "affiliations": []}, {"id": null, "name": "Amitava Das", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | A community in a social network is considered to be a group of nodes densely connected internally and sparsely connected externally.Although previous work intensely studied network topology within a community, its semantic interpretation is hardly understood. In this paper, we attempt to understand whether individuals ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11078", "DOI": "10.1609/aaai.v31i1.11078"} | ["Computer Science"] |
official:AAAI:7d4dac7aef010768d6a19b0d | 10.1609/aaai.v31i1.10914 | Scalable Algorithm for Higher-Order Co-Clustering via Random Sampling | 2,017 | null | ["ConferencePaper"] | 3 | AAAI | [{"id": null, "name": "Daisuke Hatano", "affiliations": []}, {"id": null, "name": "Takuro Fukunaga", "affiliations": []}, {"id": null, "name": "Takanori Maehara", "affiliations": []}, {"id": null, "name": "Ken-ichi Kawarabayashi", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We propose a scalable and efficient algorithm for coclustering a higher-order tensor. Viewing tensors with hypergraphs, we propose formulating the co-clustering of a tensor as a problem of partitioning the corresponding hypergraph. Our algorithm is based on the random sampling technique, which has been successfully app... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10914", "DOI": "10.1609/aaai.v31i1.10914"} | ["Computer Science"] |
official:AAAI:cdeb25bd675328837f03732c | 10.1609/aaai.v31i1.10907 | Label Efficient Learning by Exploiting Multi-Class Output Codes | 2,017 | null | ["ConferencePaper"] | 1 | AAAI | [{"id": null, "name": "Maria Balcan", "affiliations": []}, {"id": null, "name": "Travis Dick", "affiliations": []}, {"id": null, "name": "Yishay Mansour", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | We present a new perspective on the popular multi-class algorithmic techniques of one-vs-all and error correcting output codes. Rather than studying the behavior of these techniques for supervised learning, we establish a connection between the success of these methods and the existence of label-efficient learning proc... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10907", "DOI": "10.1609/aaai.v31i1.10907"} | ["Computer Science"] |
official:AAAI:df13d9f4a5c621885e64ca38 | 10.1609/aaai.v31i1.10539 | From Semantic Models to Cognitive Buildings | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Joern Ploennigs", "affiliations": []}, {"id": null, "name": "Anika Schumann", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Today's operation of buildings is either based on simple dashboards that are not scalable to thousands of sensor data or on rules that provide very limited fault information only. In either case considerable manual effort is required for diagnosing building operation problems related to energy usage or occupant comfort... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10539", "DOI": "10.1609/aaai.v31i1.10539"} | ["Computer Science"] |
official:AAAI:c9cf884aa01cc67f915cd429 | 10.1609/aaai.v31i1.10727 | Coupling Implicit and Explicit Knowledge for Customer Volume Prediction | 2,017 | null | ["ConferencePaper"] | 4 | AAAI | [{"id": null, "name": "Jingyuan Wang", "affiliations": []}, {"id": null, "name": "Yating Lin", "affiliations": []}, {"id": null, "name": "Junjie Wu", "affiliations": []}, {"id": null, "name": "Zhong Wang", "affiliations": []}, {"id": null, "name": "Zhang Xiong", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Customer volume prediction, which predicts the volume from a customer source to a service place, is a very important technique for location selection, market investigation, and other related applications. Most of traditional methods only make use of partial information for either supervised or unsupervised modeling, wh... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10727", "DOI": "10.1609/aaai.v31i1.10727"} | ["Computer Science"] |
official:AAAI:f57ac0f4aa9d8ef8ff557994 | 10.1609/aaai.v31i1.10901 | Cross-Domain Kernel Induction for Transfer Learning | 2,017 | null | ["ConferencePaper"] | 5 | AAAI | [{"id": null, "name": "Wei-Cheng Chang", "affiliations": []}, {"id": null, "name": "Yuexin Wu", "affiliations": []}, {"id": null, "name": "Hanxiao Liu", "affiliations": []}, {"id": null, "name": "Yiming Yang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | The key question in transfer learning (TL) research is how to make model induction transferable across different domains. Common methods so far require source and target domains to have a shared/homogeneous feature space, or the projection of features from heterogeneous domains onto a shared space. This paper proposes ... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10901", "DOI": "10.1609/aaai.v31i1.10901"} | ["Computer Science"] |
official:AAAI:75fccc75845456ce9e9d1348 | 10.1609/aaai.v31i1.11152 | Combining Logical Abduction and Statistical Induction: Discovering Written Primitives with Human Knowledge | 2,017 | null | ["ConferencePaper"] | 2 | AAAI | [{"id": null, "name": "Wang-Zhou Dai", "affiliations": []}, {"id": null, "name": "Zhi-Hua Zhou", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | In many real tasks there are human knowledge expressed in logic formulae as well as data samples described by raw features (e.g., pixels, strings). It is popular to apply SRL or PILPtechniques to exploit human knowledge through learning of symbolic data, or statistical learning techniques to learn from the raw data sam... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11152", "DOI": "10.1609/aaai.v31i1.11152"} | ["Computer Science"] |
official:AAAI:1f109e0f173b13f03da60c72 | 10.1609/aaai.v31i1.11208 | A Multiview-Based Parameter Free Framework for Group Detection | 2,017 | null | ["ConferencePaper"] | 125 | AAAI | [{"id": null, "name": "Xuelong Li", "affiliations": []}, {"id": null, "name": "Mulin Chen", "affiliations": []}, {"id": null, "name": "Feiping Nie", "affiliations": []}, {"id": null, "name": "Qi Wang", "affiliations": []}] | null | [] | Computer Science | null | null | false | null | Group detection is fundamentally important for analyzing crowd behaviors, and has attracted plenty of attention in artificial intelligence. However, existing works mostly have limitations due to the insufficient utilization of crowd properties and the arbitrary processing of individuals. In this paper,we propose the Mu... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.11208", "DOI": "10.1609/aaai.v31i1.11208"} | ["Computer Science"] |
official:AAAI:c4801c89dbc9f56fd541c00f | 10.1609/aaai.v31i1.10976 | Mechanism-Aware Neural Machine for Dialogue Response Generation | 2,017 | null | ["ConferencePaper"] | 13 | AAAI | [{"id": null, "name": "Ganbin Zhou", "affiliations": []}, {"id": null, "name": "Ping Luo", "affiliations": []}, {"id": null, "name": "Rongyu Cao", "affiliations": []}, {"id": null, "name": "Fen Lin", "affiliations": []}, {"id": null, "name": "Bo Chen", "affiliations": []}, {"id": null, "name": "Qing He", "affiliations"... | null | [] | Computer Science | null | null | false | null | To the same utterance, people's responses in everyday dialogue may be diverse largely in terms of content semantics, speaking styles, communication intentions and so on. Previous generative conversational models ignore these 1-to-n relationships between a post to its diverse responses, and tend to return high-frequency... | C | {"URL": "https://doi.org/10.1609/aaai.v31i1.10976", "DOI": "10.1609/aaai.v31i1.10976"} | ["Computer Science"] |
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