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Your search keyword '"Hu, Jianhao"' showing total 29 results
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29 results on '"Hu, Jianhao"'

1. Stochastic Multivariate Universal-Radix Finite-State Machine: a Theoretically and Practically Elegant Nonlinear Function Approximator

Author

Feng, Xincheng, Shen, Guodong, Hu, Jianhao, Li, Meng, and Wong, Ngai

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Nonlinearities are crucial for capturing complex input-output relationships especially in deep neural networks. However, nonlinear functions often incur various hardware and compute overheads. Meanwhile, stochastic computing (SC) has emerged as a promising approach to tackle this challenge by trading output precision for hardware simplicity. To this end, this paper proposes a first-of-its-kind stochastic multivariate universal-radix finite-state machine (SMURF) that harnesses SC for hardware-simplistic multivariate nonlinear function generation at high accuracy. We present the finite-state machine (FSM) architecture for SMURF, as well as analytical derivations of sampling gate coefficients for accurately approximating generic nonlinear functions. Experiments demonstrate the superiority of SMURF, requiring only 16.07% area and 14.45% power consumption of Taylor-series approximation, and merely 2.22% area of look-up table (LUT) schemes.

Published
2024

2. Out of the shadow? The effect of high‐status employee departure on the performance of staying coworkers in financial brokerage firms.

Author

Wang, Pengfei, Hu, Jianhao, and Liu, Jingjiang

Subjects
CONFIDENCE intervals, INDEPENDENT variables, SOCIAL capital, LABOR turnover, PRE-tests & post-tests, MATHEMATICAL variables, EMPLOYEE orientation, T-test (Statistics), BUSINESS, EMPLOYEES' workload, HYPOTHESIS, RESOURCE allocation, DESCRIPTIVE statistics, RESEARCH funding, FINANCIAL management, JOB performance
Abstract

Because high‐status employees make disproportional contributions to firms, prior literature suggests that their departure would undermine various organizational outcomes. Building on recent literature, however, we suspect that a high‐status employee may have seized disproportional resources and credits from coworkers, thereby restricting them from performing, particularly when the work context is more independent and contested. As a result, the departure of a high‐status employee may bring staying coworkers more resources and incentives to perform, causing their performance to improve. To test this possibility, we examine the effect of high‐status analysts' departure on the individual performance of analysts who remain, using a sample of sell‐side analysts in Chinese financial brokerage firms. Employing a before‐and‐after treatment research design, we find evidence that after the departure of a high‐status analyst, the staying coworkers' individual performance is significantly improved. It is particularly so when they share greater industry overlap with the departing analyst. Our extensional analyses also investigate additional contingencies, which helps provide valuable hints about possible mechanisms. [ABSTRACT FROM AUTHOR]

Published
2024
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9. Patterns of Technological Entrepreneurship and Their Determinants: Evidence from Technology-Based Manufacturing Firms in China.

Author

Liu, Jingjiang, Hu, Jianhao, Wu, Dong, and Chen, Jin

Subjects
ENTREPRENEURSHIP, EMERGING markets, VALUE capture, BUSINESS enterprises, COMPETITIVE advantage in business
Abstract

In this study, we argue that managing technological entrepreneurship effectively is crucial for firms' competitive advantage and high performance. By using an inductive approach of a multiple-case study of Chinese technology-based manufacturing firms, we identify four complementary patterns of technological entrepreneurship (i.e. in-house R&D, R&D acquisition, R&D alliance, and R&D contracting) and find that possessing the uniqueness of knowledge assets and technological capabilities and capturing the value of knowledge assets and technological capabilities are the major determinants for firms to choose these patterns. Our study develops an integrative framework of technological entrepreneurship for emerging economy firms. Implications for theory, practice, and policy are discussed. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Low Complexity State Metric Memory Reduction for Turbo Decoding With Stochastic Quantization

Author

Hu, Shuai, Han, Kaining, and Hu, Jianhao

Abstract

The size of the state metrics cache (SMC) has a predominant impact on the overall hardware consumption of the Turbo decoder. This brief presents a low complexity SMC reduction algorithm based on the proposed stochastic quantization (SQ) technique, which reduces the size of the SMC by randomly quantizing the state metrics to different small bit-width numbers. The selection of the random source and the updating method of the extrinsic information are further explored to minimize the performance loss caused by bit-width reduction. The simulation and synthesis results show that the proposed algorithm can achieve the best bit error rate (BER) performance with the lowest hardware consumption among the compared SMC reduction algorithms.

Published
2024
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