Search Results for author:
Found 12 papers, 5 papers with code
GPR Full-Waveform Inversion through Adaptive Filtering of Model Parameters and Gradients Using CNN
GPR full-waveform inversion optimizes the subsurface property model iteratively to match the entire waveform information.
Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language Models
Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks but their performance in complex logical reasoning tasks remains unsatisfactory.
Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative Retrieval
Generative retrieval (GR) has emerged as a transformative paradigm in search and recommender systems, leveraging numeric-based identifier representations to enhance efficiency and generalization.
LB-KBQA: Large-language-model and BERT based Knowledge-Based Question and Answering System
The natural language understanding capability has always been a barrier to the intent recognition performance of the Knowledge-Based-Question-and-Answer (KBQA) system, which arises from linguistic diversity and the newly appeared intent.
Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework
We propose a general Variational Embedding Learning Framework (VELF) for alleviating the severe cold-start problem in CTR prediction.
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy
In light of this missing, we propose the very first framework that employs neural architecture search to automatic model design for private deep learning, dubbed as DPNAS.
Joint Channel and Weight Pruning for Model Acceleration on Moblie Devices
In this paper, we present a unified framework with Joint Channel pruning and Weight pruning (JCW), and achieves a better Pareto-frontier between the latency and accuracy than previous model compression approaches.
Architecture Aware Latency Constrained Sparse Neural Networks
Acceleration of deep neural networks to meet a specific latency constraint is essential for their deployment on mobile devices.
Revisiting Parameter Sharing for Automatic Neural Channel Number Search
Nevertheless, it is unclear how parameter sharing affects the searching process.
Semi-supervised Learning with Contrastive Predicative Coding
Semi-supervised learning (SSL) provides a powerful framework for leveraging unlabeled data when labels are limited or expensive to obtain.
RaFM: Rank-Aware Factorization Machines
Factorization machines (FM) are a popular model class to learn pairwise interactions by a low-rank approximation.
Adaptive Co-weighting Deep Convolutional Features For Object Retrieval
Aggregating deep convolutional features into a global image vector has attracted sustained attention in image retrieval.
