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Jiang Qian

4 accepted papers

2022

TranSHER: Translating Knowledge Graph Embedding with Hyper-Ellipsoidal Restriction

EMNLP 2022main

Knowledge graph embedding methods are important for the knowledge graph completion (or link prediction) task.One state-of-the-art method, PairRE, leverages two separate vectors to model complex relations (i.e., 1-to-N, N-to-1, and N-to-N) in knowledge graphs. However, such a method strictly restrict…

2021

Network Pruning Using Linear Dependency Analysis on Feature Maps

ICASSP 2021accepted

Network pruning can be achieved by removing redundant channels. In this paper, we regard a channel ‘redundant’ if its output is linearly dependent with respect to those of other channels. Inspired by this, we propose an efficient pruning method, named as LDFM, by linear dependency analysis on all th…

Cited by 0SourceScholar
2021

Understanding Gradient Clipping In Incremental Gradient Methods

AISTATS 2021poster

We provide a theoretical analysis on how gradient clipping affects the convergence of the incremental gradient methods on minimizing an objective function that is the sum of a large number of component functions. We show that clipping on gradients of component functions leads to bias on the descent…

Cited by 49SourcePDFScholar
2020

Generating Reasonable Legal Text through the Combination of Language Modeling and Question Answering

IJCAI 2020poster

Due to the improvement of Language Modeling, the emerging NLP assistant tools aiming for text generation greatly reduce the human workload on writing documents. However, the generation of legal text faces greater challenges than ordinary texts because of its high requirement for keeping logic reason…