作者: 邪惡的你 時間: 2025-3-21 23:52 作者: 挫敗 時間: 2025-3-22 02:28 作者: Grating 時間: 2025-3-22 08:31
,Learning and?Revising Dynamic Temporal Theories in?the?Full Discrete Event Calculus,luents. The paper shows how XEC outperforms DEC on standard reasoning benchmarks, and how it can be used with an ILP system XHAIL to provide the first proof-of-principle demonstration of theory learning and revision in the full-featured DEC.作者: 指令 時間: 2025-3-22 10:56
0302-9743 st-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data..978-3-030-97453-4978-3-030-97454-1Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: braggadocio 時間: 2025-3-22 15:16 作者: 得意牛 時間: 2025-3-22 19:11
Embedding Models for Knowledge Graphs Induced by Clusters of Relations and Background Knowledge,e of the several semantic meanings that the very same relation may have. An experimental evaluation on . and . tasks proves the improvement yielded by the proposed approach (coupled with different optimizers) compared to some baseline models.作者: 集聚成團 時間: 2025-3-22 22:39 作者: 澄清 時間: 2025-3-23 05:06 作者: 入會 時間: 2025-3-23 06:12 作者: 敬禮 時間: 2025-3-23 13:45
Feature Learning by Least Generalization, features from training data and classify test data in around 90% accuracies. The results of this paper show potentials of induction and symbolic reasoning to feature learning or pattern recognition from raw data.作者: 詞匯記憶方法 時間: 2025-3-23 14:58 作者: 螢火蟲 時間: 2025-3-23 21:16 作者: 招惹 時間: 2025-3-23 23:05
Synthetic Datasets and Evaluation Tools for Inductive Neural Reasoning,s of rules or dependencies between rules are neglected. Moreover, for the development of neural approaches, we need large amounts of data to learn from and adequate, approximate evaluation measures. In this paper, we provide a tool for generating diverse datasets and for evaluating neural rule learning systems, including novel performance metrics.作者: Grasping 時間: 2025-3-24 03:06
Machine Learning of Microbial Interactions Using Abductive ILP and Hypothesis Frequency/Compressionotstrapping, re-sampling procedure. We evaluate our proposed framework on simulated data previously used to benchmark statistical interaction inference tools. Our approach has comparable accuracy to SparCC, which is one of the state-of-the-art statistical interaction inference algorithms, but with t作者: Junction 時間: 2025-3-24 09:25
,Using Domain-Knowledge to?Assist Lead Discovery in?Early-Stage Drug Design,stributions. The design consists of generators (to approximate . and .) and a discriminator (to approximate .. We investigate our approach using the well-studied problem of inhibitors for the Janus kinase (JAK) class of proteins. We assume first that if no data on inhibitors are available for a targ作者: WAX 時間: 2025-3-24 12:14
,Ontology Graph Embeddings and?ILP for?Financial Forecasting, and managers, which are then used as background predicates in addition to the relations linking companies and staff present in the ontology, and the values of the target predicate for a given time period. Progol [.] is used to learn from this mixture of predicates combining numerical with structura作者: 雄偉 時間: 2025-3-24 16:15 作者: fiscal 時間: 2025-3-24 19:28 作者: alcoholism 時間: 2025-3-24 23:58 作者: PRO 時間: 2025-3-25 06:08
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits,lational data while being robust to missing, out-of-domain data and partial counts. We show that our method generalizes to different distributions outperforming strong baselines. Moreover, due to the clear probabilistic semantics of MSPNs we have informative model interpretations.作者: 知識 時間: 2025-3-25 10:54 作者: fixed-joint 時間: 2025-3-25 14:20 作者: 銀版照相 時間: 2025-3-25 16:08
Fabrizio Ventola,Devendra Singh Dhami,Kristian Kersting the principles, with supporting examples. These principles are the conceptual counterparts of security-related error patterns that have been recurring in software and system designs for over 50 years...The boo978-3-030-33649-3Series ISSN 1619-7100 Series E-ISSN 2197-845X 作者: 節(jié)約 時間: 2025-3-25 20:05 作者: 不如樂死去 時間: 2025-3-26 00:32
Devendra Singh Dhami,Siwen Yan,Gautam Kunapuli,Sriraam Natarajan作者: CORD 時間: 2025-3-26 06:02
Leticia Freire de Figueiredo,Aline Paes,Gerson Zaverucha作者: galley 時間: 2025-3-26 11:18
mon permissions. Our evaluation over a broad spectrum of Android OSes, devices, and IMEs suggests such issue should be fixed immediately. All Android versions and most IME apps are vulnerable and private information, like contact names, location, etc., can be easily exfiltrated. Up to hundreds of mi作者: 排名真古怪 時間: 2025-3-26 15:16 作者: JOT 時間: 2025-3-26 20:07
Jáchym Barvínek,Timothy van Bremen,Yuyi Wang,Filip ?elezny,Ond?ej Ku?elkaand construct two schemes for computing polynomials of high degree on the outsourced data. Our schemes allow ., ., and . of computation results. Both schemes allow new elements to be added to each outsourced dataset. The second scheme also allows new datasets to be added. A unique feature of our sch作者: 自愛 時間: 2025-3-26 22:01 作者: judicial 時間: 2025-3-27 05:09 作者: 柏樹 時間: 2025-3-27 07:35
improve the user experience, popular IMEs integrate personalized features like reordering suggestion list of words based on user’s input history, which inevitably turn them into the vaults of user’s secret. In this paper, we make the first attempt to evaluate the security implications of IME persona作者: 無所不知 時間: 2025-3-27 13:11
Claudia d’Amato,Nicola Flavio Quatraro,Nicola Fanizzis, typically by scanning a database of records for a close enough match. In this work, we investigate the privacy-preserving biometric identification outsourcing problem, where the database owner outsources both the large-scale encrypted database and the computationally intensive identification job 作者: MULTI 時間: 2025-3-27 16:32 作者: Obvious 時間: 2025-3-27 21:47
Didac Barroso-Bergada,Alireza Tamaddoni-Nezhad,Stephen H. Muggleton,Corinne Vacher,Nika Galic,David improve the user experience, popular IMEs integrate personalized features like reordering suggestion list of words based on user’s input history, which inevitably turn them into the vaults of user’s secret. In this paper, we make the first attempt to evaluate the security implications of IME persona作者: floodgate 時間: 2025-3-28 00:27
Dany Varghese,Roman Bauer,Daniel Baxter-Beard,Stephen Muggleton,Alireza Tamaddoni-Nezhadior undergrad or first-year graduate students, also suitable.This book provides a concise yet comprehensive overview of computer and Internet security, suitable for a one-term introductory course for junior/senior undergrad or first-year graduate students. It is also suitable for self-study by anyon作者: GOAT 時間: 2025-3-28 02:06 作者: asthma 時間: 2025-3-28 07:29 作者: Mercurial 時間: 2025-3-28 10:52
Embedding Models for Knowledge Graphs Induced by Clusters of Relations and Background Knowledge,e semantically aware by exploiting the intended semantics in the KG. The method exploits schema axioms to encode knowledge that is observed as well as derived by reasoning. More knowledge is further exploited by relying on a successive hierarchical clustering process applied to relations, to make us作者: 諂媚于性 時間: 2025-3-28 16:06
Automatic Conjecturing of P-Recursions Using Lifted Inference,mated fashion, by casting them as first-order model counting problems. Algorithms for this problem typically output a single number, which is the number of models of the first-order logic sentence in question on a given domain. However, in the combinatorics setting, we are more interested in obtaini作者: octogenarian 時間: 2025-3-28 22:34
Machine Learning of Microbial Interactions Using Abductive ILP and Hypothesis Frequency/Compressioncrobiota. Many statistical approaches have been proposed to infer these interactions from microbial abundance information. However, these statistical approaches have no general mechanisms for incorporating existing ecological knowledge in the inference process. We propose an Abductive/Inductive Logi作者: nonplus 時間: 2025-3-29 02:51 作者: 制定法律 時間: 2025-3-29 03:48
Synthetic Datasets and Evaluation Tools for Inductive Neural Reasoning,e induction process. However, we argue that existing datasets and evaluation approaches are lacking in various dimensions; for example, different kinds of rules or dependencies between rules are neglected. Moreover, for the development of neural approaches, we need large amounts of data to learn fro作者: debris 時間: 2025-3-29 08:57 作者: Allege 時間: 2025-3-29 13:28 作者: cardiac-arrest 時間: 2025-3-29 16:58 作者: 觀察 時間: 2025-3-29 19:50 作者: 遺傳學 時間: 2025-3-30 00:54 作者: FEMUR 時間: 2025-3-30 07:09
Programmatic Policy Extraction by Iterative Local Search,interpretable, amenable to formal verification, or generalize better. While efficient algorithms for learning neural policies exist, learning programmatic policies is challenging. Combining imitation-projection and dataset aggregation with a local search heuristic, we present a simple and direct app作者: Myofibrils 時間: 2025-3-30 11:34 作者: Heart-Rate 時間: 2025-3-30 14:34
A First Step Towards Even More Sparse Encodings of Probability Distributions,n exponential number of values. Hence, we propose a method for extracting first-order formulas from probability distributions that require significantly less values by reducing the number of values in a distribution and then extracting, for each value, a logical formula to be further minimized. This作者: 寵愛 時間: 2025-3-30 19:21 作者: HERTZ 時間: 2025-3-30 21:07
,Learning Logic Programs Using Neural Networks by?Exploiting Symbolic Invariance,IT algorithms have mainly been implemented in the symbolic method, but they are not robust to noisy or missing data. Recently, research works combining logical operations with neural networks are receiving a lot of attention, with most works taking an extraction based approach where a single neural 作者: AVID 時間: 2025-3-31 02:30 作者: curriculum 時間: 2025-3-31 05:34
Human-Like Rule Learning from Images Using One-Shot Hypothesis Derivation,ple. Humans achieve this ability using background knowledge. Rule-based machine learning approaches such as Inductive Logic Programming (ILP) provide a framework for incorporating domain specific background knowledge. These approaches have the potential for human-like learning from small data or eve作者: Engaged 時間: 2025-3-31 10:37
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits,t hand. Recently, a clear connection between predictive modelling such as decision trees and probabilistic circuits, a form of deep probabilistic model, has been established although it is limited to propositional data. We introduce the first connection between relational rule models and probabilist作者: Longitude 時間: 2025-3-31 15:27 作者: Sleep-Paralysis 時間: 2025-3-31 17:34
