Tao Liu

Consideration for Running Data Center at High Temperatures and Using Free Air Cooling

2015

The advent of the big data era, the rapid development of mobile internet, and the rising demand of cloud computing services require increasingly more compute capability from their data center. This compute increase will most …

A Theorem Prover for Quantum Hoare Logic and Its Applications

2016 · arXiv (Cornell University)

Quantum Hoare Logic (QHL) was introduced in Ying's work to specify and reason about quantum programs. In this paper, we implement a theorem prover for QHL based on Isabelle/HOL. By applying the theorem prover, verifying …

Automatic Clustering Algorithm for Movie Recommendation Based on LFM Model

2017 · DEStech Transactions on Computer Science and Engineering

In order to enhance audience satisfaction and recommend them different types of movies, it is necessary to point out the concept, latent factor model (hereinafter referred to as LFM). By using clustering analysis technology, users …

Subword-level Composition Functions for Learning Word Embeddings

2018

Subword-level information is crucial for capturing the meaning and morphology of words, especially for out-of-vocabulary entries. We propose CNN-and RNN-based subword-level composition functions for learning word embeddings, and systematically compare them with popular word-level and …

High-precision nonlocal temporal correlation identification of entangled photon pairs for quantum clock synchronization

2020 · Review of Scientific Instruments

High-precision nonlocal temporal correlation identification in entangled photon pairs is critical to measure the time offset between remote independent time scales for many quantum information applications. The first nonlocal correlation identification was reported in 2009, …

Glint: Decentralized Federated Graph Learning with Traffic Throttling and Flow Scheduling

2021

Federated learning has been proposed as a promising distributed machine learning paradigm with strong privacy protection on training data. Existing work mainly focuses on training convolutional neural network (CNN) models good at learning on image/voice …

Fast Global Convergence of Policy Optimization for Constrained MDPs.

2021 · arXiv (Cornell University)

We address the issue of safety in reinforcement learning. We pose the problem in a discounted infinite-horizon constrained Markov decision process framework. Existing results have shown that gradient-based methods are able to achieve an $\mathcal{O}(1/\sqrt{T})$ …

Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation

2023 · arXiv (Cornell University)

We study robust reinforcement learning (RL) with the goal of determining a well-performing policy that is robust against model mismatch between the training simulator and the testing environment. Previous policy-based robust RL algorithms mainly focus …

Information Dropping Data Augmentation for Machine Translation Quality Estimation

2024 · IEEE/ACM Transactions on Audio Speech and Language Processing

Machine translation quality estimation (QE) refers to the quality assessment of machine translations without a given reference translation. Supervised QE models based on neural networks have achieved state-of-the-art results. But this method requires large-scale training …

Automatic Modulation Classification Under Large Frequency Offset: A Robust Approach Integrating Pre-classification and Compensation Mechanism

2024

Automatic Modulation Classification (AMC) is a critical technology in the field of non-cooperative communication. Carrier frequency offset is an inevitable impairment factor in communication systems, and it significantly affects the performance of AMC, especially when …

Act in Collusion: Distributed Multi-Target Backdoor Attacks in Federated Learning

2024 · arXiv (Cornell University)

Federated learning (FL) is widely used in Internet-of-Things (IoT) systems, but its distributed training process also exposes it to backdoor attacks. Existing studies mainly consider single-target or centralized multi-target settings, while coordinated distributed multi-target attacks …

Clustering and Anomaly Detection of Users Based on Seasonal Load Characteristics

2024

Accurate implementation of load clustering analysis can improve the accuracy of forecasting future load demand, which is more helpful for power system planners to better adjust the balance of power supply and demand, and reasonably …

Cross-sector deep learning scales life cycle assessment using unified textual descriptions

2026 · Environmental Science and Ecotechnology

Life cycle assessment (LCA) is a foundational framework for quantifying global environmental impacts to guide decarbonization and circular economy transitions. Yet, conventional inventory compilation remains severely bottlenecked by data scarcity and intensive manual curation, with …

Analogical Reasoning on Chinese Morphological and Semantic Relations

2018

Analogical reasoning is effective in capturing linguistic regularities. This paper proposes an analogical reasoning task on Chinese. After delving into Chinese lexical knowledge, we sketch 68 implicit morphological relations and 28 explicit semantic relations. A …