Junyi Li

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Qualcomm ∙ University of Pittsburgh

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Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning

In the paper, we propose an effective and efficient Compositional Federa...
06/21/2021 ∙ by Feihu Huang, et al. ∙ 7 ∙ share

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SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients

Adaptive gradient methods have shown excellent performance for solving m...
06/15/2021 ∙ by Feihu Huang, et al. ∙ 13 ∙ share

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Few-shot Knowledge Graph-to-Text Generation with Pretrained Language Models

This paper studies how to automatically generate a natural language text...
06/03/2021 ∙ by Junyi Li, et al. ∙ 16 ∙ share

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Pretrained Language Models for Text Generation: A Survey

Text generation has become one of the most important yet challenging tas...
05/21/2021 ∙ by Junyi Li, et al. ∙ 22 ∙ share

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Knowledge-based Review Generation by Coherence Enhanced Text Planning

As a natural language generation task, it is challenging to generate inf...
05/09/2021 ∙ by Junyi Li, et al. ∙ 6 ∙ share

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Mitigating Hand Blockage with Non-Directional Beamforming Codebooks

Hand blockage leads to significant performance impairments at millimeter...
04/13/2021 ∙ by Vasanthan Raghavan, et al. ∙ 0 ∙ share

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TextBox: A Unified, Modularized, and Extensible Framework for Text Generation

We release an open library, called TextBox, which provides a unified, mo...
01/06/2021 ∙ by Junyi Li, et al. ∙ 8 ∙ share

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Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network

Personalized review generation (PRG) aims to automatically produce revie...
10/04/2020 ∙ by Junyi Li, et al. ∙ 6 ∙ share

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Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee

Due to the hierarchical structure of many machine learning problems, bil...
09/01/2020 ∙ by Junyi Li, et al. ∙ 16 ∙ share

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Faster Secure Data Mining via Distributed Homomorphic Encryption

Due to the rising privacy demand in data mining, Homomorphic Encryption ...
06/17/2020 ∙ by Junyi Li, et al. ∙ 0 ∙ share

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Generating Realistic Stock Market Order Streams

We propose an approach to generate realistic and high-fidelity stock mar...
06/07/2020 ∙ by Junyi Li, et al. ∙ 0 ∙ share

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CLUE: A Chinese Language Understanding Evaluation Benchmark

We introduce CLUE, a Chinese Language Understanding Evaluation benchmark...
04/13/2020 ∙ by Liang Xu, et al. ∙ 0 ∙ share

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Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning

The task of Knowledge Graph Completion (KGC) aims to automatically infer...
03/28/2020 ∙ by Gaole He, et al. ∙ 3 ∙ share

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Hand and Body Blockage Measurements with Form-Factor User Equipment at 28 GHz

Blockage by the human hand/body is an important impairment in realizing ...
12/08/2019 ∙ by Vasanthan Raghavan, et al. ∙ 0 ∙ share

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Generating Long and Informative Reviews with Aspect-Aware Coarse-to-Fine Decoding

Generating long and informative review text is a challenging natural lan...
06/11/2019 ∙ by Junyi Li, et al. ∙ 0 ∙ share

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Evolution of Physical-Layer Communications Research in the Post-5G Era

The evolving Fifth Generation New Radio (5G-NR) cellular standardization...
01/04/2019 ∙ by Vasanthan Raghavan, et al. ∙ 0 ∙ share

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Antenna Placement and Performance Tradeoffs with Hand Blockage in Millimeter Wave Systems

The ongoing commercial deployment of millimeter wave systems brings into...
01/04/2019 ∙ by Vasanthan Raghavan, et al. ∙ 0 ∙ share

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Investigation of Performance in Integrated Access and Backhaul Networks

Wireless backhaul allows densification of mobile networks without incurr...
04/01/2018 ∙ by Muhammad Nazmul Islam, et al. ∙ 0 ∙ share

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Channel Reconstruction-Based Hybrid Precoding for Millimeter Wave Multi-User MIMO Systems

The focus of this paper is on multi-user MIMO transmissions for millimet...
02/14/2018 ∙ by Miguel R. Castellanos, et al. ∙ 0 ∙ share

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Statistical Blockage Modeling and Robustness of Beamforming in Millimeter Wave Systems

There has been a growing interest in the commercialization of millimeter...
01/10/2018 ∙ by Vasanthan Raghavan, et al. ∙ 0 ∙ share

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