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pro vyhledávání: '"Peng, Xiangjun"'
Autor:
Peng, Xiangjun
This work provides new insights and constructs to the field of computer architecture and systems, and these insights are expected to be useful for the broad software stack. First, this work introduces Functionality Locality: this form of Functionalit
Externí odkaz:
http://arxiv.org/abs/2404.11721
Autor:
Peng, Xiangjun
A new analytic framework is first formalized via the usage of the Monadology (Leibniz 1898), to expand the understanding of Zermelo-Fraenkel-choice set theory (ZFC) and Von Neumann-Bernays-Godel set theory (NBG). Implicitly, the framework levels valu
Externí odkaz:
http://arxiv.org/abs/2404.00404
This paper introduces the first formalization, implementation and quantitative evaluation of Feint in Multi-Player Games. Our work first formalizes Feint from the perspective of Multi-Player Games, in terms of the temporal, spatial, and their collect
Externí odkaz:
http://arxiv.org/abs/2403.07932
Feint actions refer to a set of deceptive actions, which enable players to obtain temporal advantages from their opponents. Such actions are regarded as widely-used tactic in most non-deterministic Two-player Games (e.g. boxing and fencing). However,
Externí odkaz:
http://arxiv.org/abs/2403.07931
Autor:
Peng, Xiangjun
This work presents a discovery to advance the wisdom in a particular Succinct Data Structure: Wavelet Tree (Grossi, Gupta, and Vitter 2003). The discovery is first made by showing the feasibility of Reversed Indexes = Values: for integers within $[0,
Externí odkaz:
http://arxiv.org/abs/2311.09522
Autor:
Liu, Junyu, Jin, Wangkai, He, Zhenyong, Ming, Xiaoxing, Duan, Yicun, Xiong, Zeyu, Peng, Xiangjun
The emerging trends of Internet-of-Vehicles (IoV) demand centralized servers to collect/process sensitive data with limited computational resources on a single vehicle. Such centralizations of sensitive data demand practical privacy protections. One
Externí odkaz:
http://arxiv.org/abs/2202.06495
Emerging Autonomous Vehicles (AV) breed great potentials to exploit data-driven techniques for adaptive and personalized Human-Vehicle Interactions. However, the lack of high-quality and rich data supports limits the opportunities to explore the desi
Externí odkaz:
http://arxiv.org/abs/2202.06494
Recent developments of advanced Human-Vehicle Interactions rely on the concept Internet-of-Vehicles (IoV), to achieve large-scale communications and synchronizations of data in practice. The concept of IoV is highly similar to a distributed system, w
Externí odkaz:
http://arxiv.org/abs/2202.06477
The challenges of polyphonic sound event detection (PSED) stem from the detection of multiple overlapping events in a time series. Recent efforts exploit Deep Neural Networks (DNNs) on Time-Frequency Representations (TFRs) of audio clips as model inp
Externí odkaz:
http://arxiv.org/abs/2111.12869
Autor:
Wang, Yaohua, Orosa, Lois, Peng, Xiangjun, Guo, Yang, Ghose, Saugata, Patel, Minesh, Kim, Jeremie S., Luna, Juan Gómez, Sadrosadati, Mohammad, Ghiasi, Nika Mansouri, Mutlu, Onur
DRAM Main memory is a performance bottleneck for many applications due to the high access latency. In-DRAM caches work to mitigate this latency by augmenting regular-latency DRAM with small-but-fast regions of DRAM that serve as a cache for the data
Externí odkaz:
http://arxiv.org/abs/2009.08437