Karp's Theorem in Inverse Obstacle Scattering Problems

In this work, we provide a proof of the so-called Karp's theorem in a different approach. We use the unique continuation principle together with the monotonicity of eigenvalues for the negative Laplace operator. This method is new and would be applicable to other types of inverse scattering problems

Towards Deep Attention in Graph Neural Networks: Problems and Remedies

Graph neural networks (GNNs) learn the representation of graph-structured data, and their expressiveness can be further enhanced by inferring node relations for propagation. Attention-based GNNs infer neighbor importance to manipulate the weight of its propagation. Despite their popularity, the discussion on deep graph attention and its unique challenges has been limited. In this work, we investigate some problematic phenomena related to deep graph attention, including vulnerability to over-smoothed features and smooth cumulative attention. Through theoretical and empirical analyses, we show that various attention-based GNNs suffer from these problems. Motivated by our findings, we propose AEROGNN, a novel GNN architecture designed for deep graph attention. AERO-GNN provably mitigates the proposed problems of deep graph attention, which is further empirically demonstrated with (a) its adaptive and less smooth attention functions and (b) higher performance at deep layers (up to 64). On 9 out of 12 node classification benchmarks, AERO-GNN outperforms the baseline GNNs, highlighting the advantages of deep graph attention. Our code is available at https://github.com/syleeheal/AERO-GNN.Comment: 22 pages, 6 figures, conference paper, published in International Conference on Machine Learning. PMLR, 202

How Transitive Are Real-World Group Interactions? -- Measurement and Reproduction

Many real-world interactions (e.g., researcher collaborations and email communication) occur among multiple entities. These group interactions are naturally modeled as hypergraphs. In graphs, transitivity is helpful to understand the connections between node pairs sharing a neighbor, and it has extensive applications in various domains. Hypergraphs, an extension of graphs, are designed to represent group relations. However, to the best of our knowledge, there has been no examination regarding the transitivity of real-world group interactions. In this work, we investigate the transitivity of group interactions in real-world hypergraphs. We first suggest intuitive axioms as necessary characteristics of hypergraph transitivity measures. Then, we propose a principled hypergraph transitivity measure HyperTrans, which satisfies all the proposed axioms, with a fast computation algorithm Fast-HyperTrans. After that, we analyze the transitivity patterns in real-world hypergraphs distinguished from those in random hypergraphs. Lastly, we propose a scalable hypergraph generator THera. It reproduces the observed transitivity patterns by leveraging community structures, which are pervasive in real-world hypergraphs. Our code and datasets are available at https://github.com/kswoo97/hypertrans.Comment: To be published in KDD 2023. 12 pages, 7 figures, and 11 table

FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning

Psychiatrists diagnose mental disorders via the linguistic use of patients. Still, due to data privacy, existing passive mental health monitoring systems use alternative features such as activity, app usage, and location via mobile devices. We propose FedTherapist, a mobile mental health monitoring system that utilizes continuous speech and keyboard input in a privacy-preserving way via federated learning. We explore multiple model designs by comparing their performance and overhead for FedTherapist to overcome the complex nature of on-device language model training on smartphones. We further propose a Context-Aware Language Learning (CALL) methodology to effectively utilize smartphones' large and noisy text for mental health signal sensing. Our IRB-approved evaluation of the prediction of self-reported depression, stress, anxiety, and mood from 46 participants shows higher accuracy of FedTherapist compared with the performance with non-language features, achieving 0.15 AUROC improvement and 8.21% MAE reduction.Comment: Accepted to the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023

The cities of spanish in the county of Cumaná during the government of Espinosa de los Monteros

Artículo de la sección: EstudiosUtilizando como fuente los padrones y matrículas de población realizados por el gobernador Espinosa de los Monteros durante su visita a la provincia de Cumaná, este artículo estudia los modelos de asentamiento de las siguientes ciudades de españoles: Cumanacoa, Cariaco, Campano, Río Caribes y Araya. Dicha visita posee un gran valor histórico por su riqueza informativa y por ser un documento fundamental para el conocimiento de la situación demográfica de Cumaná en tomo al año 1745. En este trabajo se presta atención a la evolución demográfica de la región, estmctura familiar, composición y tamaño de los hogares, la posición social y económica de sus pobladores, así como al tipo y número de viviendas.Using as source the censures and population’s registrations carried out by the governor Espinosa de los Monteros during their visit for the county of Cumaná, this article studies the models of establishment of the following cities of Spaniards: Cumanacoa, Cariaco, Campano, Río Caribes and Araya. This visit possesses a great historical value for its informative wealth and to be a fundamental document for the knowledge of the demographic situation of Cumaná around the year 1745. In this work attention is paid to the demographic evolution of the region, it structures family, composition and size of the homes, the social and economic position of its residents, as well as the type and number of housings.Departamento de Historia Moderna y de América, Universidad de Granad