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- Minwei Feng, Bing Xiang, Michael R. Glass, Lidan Wang, Bowen Zhou
- ASRU
- 2015

We apply a general deep learning framework to address the non-factoid question answering task. Our approach does not rely on any linguistic tools and can be applied to different languages or domains. Various architectures are presented and compared. We create and release a QA corpus and setup a new QA task in the insurance domain. Experimental results… (More)

- Julie Qiaojin Lin, Tamer Elsayed, Lidan Wang, Donald Metzler
- TREC
- 2009

This paper describes Ivory, an attempt to build a distributed retrieval system around the open-source Hadoop implementation of MapReduce. We focus on three noteworthy aspects of our work: a retrieval architecture built directly on the Hadoop Distributed File System (HDFS), a scalable MapReduce algorithm for inverted indexing, and webpage classification to… (More)

- Lidan Wang, Paul N. Bennett, Kevyn Collins-Thompson
- SIGIR
- 2012

Many techniques for improving search result quality have been proposed. Typically, these techniques increase average effectiveness by devising advanced ranking features and/or by developing sophisticated learning to rank algorithms. However, while these approaches typically improve average performance of search results relative to simple baselines, they… (More)

- Lidan Wang, Julie Qiaojin Lin, Donald Metzler
- SIGIR
- 2010

It has been shown that learning to rank approaches are capable of learning highly effective ranking functions. However, these approaches have mostly ignored the important issue of efficiency. Given that both efficiency and effectiveness are important for real search engines, models that are optimized for effectiveness may not meet the strict efficiency… (More)

- Lidan Wang, Douglas W. Oard
- HLT-NAACL
- 2009

Computational processing of text exchanged in interactive venues in which participants engage in simultaneous conversations can benefit from techniques for automatically grouping overlapping sequences of messages into separate conversations, a problem known as “disentanglement.” While previous methods exploit both lexical and non-lexical information that… (More)

- Lidan Wang, Donald Metzler, Julie Qiaojin Lin
- CIKM
- 2010

This paper introduces the notion of temporally constrained ranked retrieval, which, given a query and a time constraint, produces the best possible ranked list within the specified time limit. Naturally, more time should translate into better results, but the ranking algorithm should always produce <i>some</i> results. This property is desirable from a… (More)

- Lidan Wang, Julie Qiaojin Lin, Donald Metzler
- SIGIR
- 2011

There is a fundamental tradeoff between effectiveness and efficiency when designing retrieval models for large-scale document collections. Effectiveness tends to derive from sophisticated ranking functions, such as those constructed using learning to rank, while efficiency gains tend to arise from improvements in query evaluation and caching strategies.… (More)

- Huamin Wang, Shukai Duan, Tingwen Huang, Lidan Wang, Chuandong Li
- IEEE Transactions on Neural Networks and Learning…
- 2017

In this brief, we establish a novel complex-valued memristive recurrent neural network (CVMRNN) to study its stability. As a generalization of real-valued memristive neural networks, CVMRNN can be separated into real and imaginary parts. By means of <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula>-matrix and Lyapunov function,… (More)

- Shukai Duan, Xiaofang Hu, Zhekang Dong, Lidan Wang, Pinaki Mazumder
- IEEE Transactions on Neural Networks and Learning…
- 2015

Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predicted in the late seventies, but it garnered nascent research interest due to the recent much-acclaimed… (More)

- Lidan Wang, Emmanuel M. Drakakis, Shukai Duan, Pengfei He, Xiaofeng Liao
- I. J. Bifurcation and Chaos
- 2012