Wei Peng

Asymptotic Distributions and Rates of Convergence for Random Forests via Generalized U-statistics

2019 · arXiv (Cornell University)

Random forests remain among the most popular off-the-shelf supervised learning algorithms. Despite their well-documented empirical success, however, until recently, few theoretical results were available to describe their performance and behavior. In this work we push …

Revealing the Invisible with Model and Data Shrinking for Composite-database Micro-expression Recognition

2020 · arXiv (Cornell University)

Composite-database micro-expression recognition is attracting increasing attention as it is more practical to real-world applications. Though the composite database provides more sample diversity for learning good representation models, the important subtle dynamics are prone to …

Quantum neural networks with deep residual learning.

2020 · arXiv (Cornell University)

Inspired by the success of neural networks in the classical machine learning tasks, there has been tremendous effort to develop quantum neural networks (QNNs), especially for quantum data or tasks that are inherently quantum in …

CogIntAc: Modeling the Relationships between Intention, Emotion and Action in Interactive Process from Cognitive Perspective

2022 · 2022 International Joint Conference on Neural Networks (IJCNN)

Intention, emotion and action are important psychological factors in human activities, which play an important role in the interaction between individuals. How to model the interaction process between individuals by analyzing the relationship of their …

Self-Adaptive Reasoning on Sub-Questions for Multi-Hop Question Answering

2023

In this paper, we present the Self-Adapting Reasoning Model (SAR) for solving multi-hop question answering (MHQA) tasks, where the QA system is supposed to find the correct answer within the given multiple documents and a …

New Datasets and Controllable Iterative Data Augmentation Method for Code-switching ASR Error Correction

2023

With the wide use of automatic speech recognition(ASR) systems, researchers pay more attention to the ASR error correction task to improve the quality of recognition results. In particular, ASR in bilingual or multilingual settings, namely …

Deep anomaly detection for time series: A survey

2025 · Computer Science Review

The cyberspace environment has evolved into a complex ecosystem, generating vast amounts of diverse time series data from various devices, systems, and software. Detecting anomalies in these massive, multi-source datasets is critical for ensuring system …

Learning to Align, Aligning to Learn: A Unified Approach for Self-Optimized Alignment

2025 · arXiv (Cornell University)

Alignment methodologies have emerged as a critical pathway for enhancing language model alignment capabilities. While SFT (supervised fine-tuning) accelerates convergence through direct token-level loss intervention, its efficacy is constrained by offline policy trajectory. In contrast, …

BLiMP: The Benchmark of Linguistic Minimal Pairs for English (Electronic Resources)

2020 · Faculty Digital Archive (New York University Florence)

We introduce The Benchmark of Linguistic Minimal Pairs (BLiMP),1 a challenge set for evaluating the linguistic knowledge of language models (LMs) on major grammatical phenomena in English. BLiMP consists of 67 individual datasets, each containing …