Jian Yang

Design of Embedded Environment Raster Data Access Engine

2015 · Computer engineering & Software

Raster data access engine as an important part of geographic information access engine is responsible for the completion of raster data storage, a library, storage and access.To solve the storage and access in resource-constrained embedded …

BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation

2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Yuchen Jiang, Tianyu Liu, Shuming Ma, Dongdong Zhang, Jian Yang, Haoyang Huang, Rico Sennrich, Ryan Cotterell, Mrinmaya Sachan, Ming Zhou. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational …

HanoiT: Enhancing Context-aware Translation via Selective Context

2023 · arXiv (Cornell University)

Context-aware neural machine translation aims to use the document-level context to improve translation quality. However, not all words in the context are helpful. The irrelevant or trivial words may bring some noise and distract the …

Machine learning platform design and application based on spark

2023

This paper proposes a design solution for a distributed machine learning platform based on Apache Spark and expounds on its advantages in specific application scenarios. Through Spark's distributed computing framework, the platform realizes efficient machine …

Wasserstein Discriminant Dictionary Learning for Graph Representation

2024 · IEEE Transactions on Pattern Analysis and Machine Intelligence

Mining discriminative graph topological information plays an important role in promoting graph representation ability. However, it suffers from two main issues: (1) the difficulty/complexity of computing global inter-class/intra-class scatters, commonly related to mean and covariance …

DWGCN: a route recommendation model based on deepwalk-graph convolutional network

2024 · IET conference proceedings.

Route Recommendation has been the foundation of trip planning, and although there are many studies in the literature, there are still many challenges. The first one is the problem of how to accurately obtain the …

TVDO: Tchebycheff Value-Decomposition Optimization for Multiagent Reinforcement Learning

2024 · IEEE Transactions on Neural Networks and Learning Systems

In cooperative multiagent reinforcement learning (MARL), centralized training with decentralized execution (CTDE) has recently attracted more attention due to the physical demand. However, the most dilemma therein is the inconsistency between jointly-trained policies and individually …

MMAR: Towards Lossless Multi-Modal Auto-Regressive Probabilistic Modeling

2024 · arXiv (Cornell University)

Recent advancements in multi-modal large language models have propelled the development of joint probabilistic models capable of both image understanding and generation. However, we have identified that recent methods suffer from loss of image information …

Advancing Textual Prompt Learning with Anchored Attributes

2024 · arXiv (Cornell University)

Textual-based prompt learning methods primarily employ multiple learnable soft prompts and hard class tokens in a cascading manner as text inputs, aiming to align image and text (category) spaces for downstream tasks. However, current training …

Weakly Supervised Object Localization With Progressive Activation Diffusion

2025 · IEEE Transactions on Neural Networks and Learning Systems

Weakly supervised object localization (WSOL) aims to locate objects with only image-level labels. Previous works mainly follow the framework of class activation map (CAM), which discovers the objects by estimating the contribution of each pixel …

RCEFL: Reputation-based Communication-aware Optimization of Federated Learning

2024

Federated learning (FL) is a privacy-preserving distributed machine learning paradigm, where multiple devices holding local datasets collaborate to train a general global model without disclosing data. Instead of submitting raw data as in centralized training, …