|Present||Associate Professor, Wright State University ‐ Computer Science and Engineering|
|Present||Director, Data-Intensive Analysis and Computing (DIAC) Lab, Wright State University ‐ Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis)|
Joshi Research Center 385
3640 Colonel Glenn Hwy
Dayton, OH 45435-0001
Conference Proceedings and Presentations (32)
PerturBoost: Practical Confidential Classifier Learning in the Cloud
Proceedings of the 13th IEEE International Conference on Data Mining (2013)
Mining large data requires intensive computing resources and data mining expertise, which might not be available for many users. With ...
Secure Computation of Top-K Eigenvectors for Shared Matrices in the ...
Proceedings of the Sixth IEEE International Conference on Cloud Computing (2013)
With the development of sensor network, mobile computing, and web applications, data are now collected from many distributed sources to ...
Privacy Preserving Boosting in the Cloud with Secure Half-Space Queries
Proceedings of the 2012 ACM Conference on Computer and Communications Security (2012)
This paper presents a preliminary study on the PerturBoost approach that aims to provide efficient and secure classifier learning in ...
Mining Privacy Settings to Find Optimal Privacy-Utility Tradeoffs for Social ...
Proceedings of the 2012 International Conference on Social Computing Privacy, Security, Risk and Trust (2012)
Privacy has been a big concern for users of social network services (SNS). On recent criticism about privacy protection, most ...
Flying under the Radar: Maintaining Control of Kernel without Changing ...
Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research (2011)
Cyber-spies rely on technologies such as rootkits to maintain a stealthy control of the victim kernel. Current techniques can detect ...
Towards Optimal Resource Provisioning for Running MapReduce Programs in Public ...
Proceedings of the 2011 IEEE International Conference on Cloud Computing (2011)
Running MapReduce programs in the public cloud introduces the important problem: how to optimize resource provisioning to minimize the financial ...
RASP: Efficient Multidimensional Range Query on Attack-Resilient Encrypted Databases
Proceedings of the first ACM Conference on Data and Application Security and Privacy (2011)
Range query is one of the most frequently used queries for online data analytics. Providing such a query service could ...
Cross-Market Model Adaptation with Pairwise Preference Data for Web Search ...
Proceedings of the 23rd International Conference on Computational Linguistics (2010)
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and ...
On Domain Similarity and Effectiveness of Adapting-to-Rank
Proceedings of the 18th ACM Conference on Information and Knowledge Management (2009)
Adapting to rank address the problem of insufficient domain-specific labeled training data in learning to rank. However, the initial study ...
VisGBT: Visually Analyzing Evolving Datasets for Adaptive Learning
Proceedings of the 5th International Conference on Collaborative Computing, Networking, Applications and Worksharing (2009)
Many machine learning problems involve changes in both feature distribution and label distribution, such as domain adaptation and learning drifting ...
Trada: Tree Based Ranking Function Adaptation
Proceedings of the 17th ACM conference on Information and knowledge Management (2008)
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions ...
A General Boosting Method and its Application to Learning Ranking ...
Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference (2007)
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many ...
Space Adaptation: Privacy-Preserving Multiparty Collaborative Mining with Geometric Perturbation
Proceedings of the Twenty-Sixth Annual ACM Symposium on Principles of Distributed Computing (2007)
The service-oriented infrastructure has become popular for collaboratively mining data distributed over organizations , where the participants are the data ...
A Regression Framework for Learning Ranking Functions using Relative Relevance ...
Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (2007)
Effective ranking functions are an essential part of commercial search engines. We focus on developing a regression framework for learning ...
Towards Attack-Resilient Geometric Data Perturbation
Proceedings of the Seventh SIAM International Conference on Data Mining (2007)
Data perturbation is a popular technique for privacy-preserving data mining. The major challenge of data perturbation is balancing privacy protection ...
Detecting the Change of Clustering Structure in Categorical Data Streams
Proceedings of the 2006 SIAM International Conference on Data Mining (2006)
Analyzing clustering structures in data streams can provide critical information for making decision in real time. In this paper, we ...
Efficiently Clustering Transactional Data with Weighted Coverage Density
CIKM '06 Proceedings of the 15th ACM International Conference on Information and Knowledge Management (2006)
It is widely recognized that developing efficient and fully automated algorithms for clustering large transactional datasets is a challenging problem. ...
Privacy-Preserving Data Classification with Rotation Perturbation
Fifth IEEE International Conference on Data Mining (2005)
This paper presents a random rotation perturbation approach for privacy preserving data classification. Concretely, we identify the importance of classification-specific ...