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To imitate the ability of keeping learning of human, continual learning which can learn from a never-ending data stream has attracted more interests recently. In all settings, the online class incremental learning (OCIL), where incoming samples from data ...

Previous work on privacy-aware ranking has addressed the minimization of information leakage when scoring top k documents, and has not studied on how to retrieve these top documents and their features for ranking. This paper proposes a privacy-...

The study of the prediction of stock market volatility is of great significance to rationally control financial market risks and increase excessive investment returns and has received extensive attention from academic and commercial circles. ...

Temporal moment localization via language aims to localize a video span in an untrimmed video which best matches the given natural language query. In most previous works, they try to match the whole query feature with multiple moment proposals, or match ...

BlockMax WAND (BMW) and its variants can effectively prune low-scoring documents for fast top-k disjunctive query processing. This paper studies a boosting approach that further accelerates document retrieval by executing BMW, or one of its variants, on ...

This paper studies privacy-aware inverted index design and document retrieval for multi-keyword document search in a trusted hardware execution environment such as Intel SGX. The previous work uses time-consuming oblivious computing techniques to avoid ...

The recent work on neural ranking has achieved solid relevance improvement, by exploring similarities between documents and queries using word embeddings. It is an open problem how to leverage such an advancement for privacy-aware ranking, which is ...

Interaction-based neural ranking has been shown to be effective for document search using distributed word representations. However the time or space required is very expensive for online query processing with neural ranking. This paper investigates ...

Tree-based ensembles are widely used for document ranking but supporting such a method efficiently under a privacy-preserving constraint on the cloud is an open research problem. The main challenge is that letting the cloud server perform ranking ...

The rapid development of the Internet facilitates the transformation to the smart park from the traditional one. The positioning function of the wireless sensor network--one of the solution of the smart park--is facing challenges on the region where a ...

This paper proposes a private ranking scheme with linear additive scoring for efficient top K keyword search on modest-sized cloud datasets. This scheme strikes for tradeoffs between privacy and efficiency by proposing single-round client-server ...

In order to solve the problem which fails to consider the degree of attribute dependence in current network access selection schemes, a novel heterogeneous network access selection scheme based on attribute dependence is proposed in this paper. The ...

Along with the increasing demands for the applications running on the wireless sensor network (WSN), energy consumption and congestion become two main problems to be resolved urgently. However, in most scenes, these two problems aren't considered ...

In crowdsensing to mobile phones, each user needs incentives to participate. Mobile devices with sensing capabilities have enabled a new paradigm of mobile crowdsensing with a broad range of applications. A major challenge in achieving stable crowdsensing ...

Network coding has been shown to be an effective approach to improve the wireless system performance. However, many security issues impede its wide deployment in practice. Besides the well-studied pollution attacks, there is another severe threat, that of ...