Results 241 to 250 of about 2,094,770 (266)
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Spatio-temporal context reduction
Proceedings of the 40th International Conference on Software Engineering, 2018Zero-day Use-After-Free (UAF) vulnerabilities are increasingly popular and highly dangerous, but few mitigations exist. We introduce a new pointer-analysis-based static analysis, CRed, for finding UAF bugs in multi-MLOC C source code efficiently and effectively.
Hua Yan +3 more
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A Distributed Representation of Temporal Context
Journal of Mathematical Psychology, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Howard, Marc W., Kahana, Michael J.
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The Successor Representation and Temporal Context
Neural Computation, 2012The successor representation was introduced into reinforcement learning by Dayan ( 1993 ) as a means of facilitating generalization between states with similar successors. Although reinforcement learning in general has been used extensively as a model of psychological and neural processes, the psychological validity of the successor representation has
Samuel J, Gershman +4 more
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Dynamic temporal interpretation contexts for temporal abstraction
Proceedings Third International Workshop on Temporal Representation and Reasoning (TIME '96), 1998The temporal-abstraction task is the task of abstracting higher-level concepts from time-stamped data in a context-sensitive manner. We have developed and implemented a formal knowledge-based framework for decomposing and solving that task that supports acquisition, maintenance, reuse, and sharing of temporal-abstraction knowledge.
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2016
Temporal database approach is one of the most significant sphere of data processing, the basic part is exact time management, changes and progress monitoring over the time. Conventional database does not support time management, historical data can be processed only partially by difficult and time consuming transformations.
Michal Kvet, Karol Matiaško
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Temporal database approach is one of the most significant sphere of data processing, the basic part is exact time management, changes and progress monitoring over the time. Conventional database does not support time management, historical data can be processed only partially by difficult and time consuming transformations.
Michal Kvet, Karol Matiaško
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Temporal Context-Aware Recommendation
2016Users’ behaviors in social media systems are generally influenced by intrinsic interest as well as the temporal context (e.g., the public’s attention at that time). In this chapter, we focus on analyzing user behaviors in social media systems and designing a latent class statistical mixture model, named temporal context-aware mixture model (TCAM), to ...
Yin, Hongzhi, Cui, Bin
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Altai megafloods—The temporal context
Earth-Science Reviews, 2020Abstract Pleistocene floods, from ice-dammed lakes in the Russian Altai Mountains, are among the largest freshwater megafloods in Earth history. Improved dating techniques have led to new dates constraining the timing of flood erosional and depositional events.
Jürgen Herget +3 more
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Temporal context in human fMRI
Current Opinion in Behavioral Sciences, 2017Memory for personally experienced events includes temporal context that allows organization and retrieval according to sequence. This review compares fMRI studies of temporal context, assessing the processes required within each paradigm. Prefrontal cortex is important for temporal sequence memory, perhaps due to its role in organizing information ...
Fang Wang, Rachel A Diana
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Spatial-Temporal Context-Aware Tracking
IEEE Signal Processing Letters, 2019Discriminative correlation filters (DCFs) have recently achieved competitive performance in visual tracking benchmarks. However, most of the existing DCF trackers only consider the spatial features of the target and could hardly benefit from the inter-frame and historical information, which may degrade the tracking performance when occlusion and ...
Yuqi Han +3 more
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Learning Temporal Context for Activity Recognition
2016We investigate how incremental learning of long-term human activity patterns improves the accuracy of activity classification over time. Rather than trying to improve the classification methods themselves, we assume that they can take into account prior probabilities of activities occurring at a particular time.
Coppola C. +3 more
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