Monthly Archives: September 2015

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    MCL Research Paper selected as the Best Paper of an ACM SIGSPATIAL Workshop

MCL Research Paper selected as the Best Paper of an ACM SIGSPATIAL Workshop

The paper “Collaborative Group-Activity Recommendation in Location-Based Social Networks” by Sanjay Purushotham*, Junaith Shahabdeen, Lama Nachman, C.-C. JayKuo, published at the Geo Crowd 2014 workshop of the ACM SIGSPATIAL Conference has been selected by the workshop organizers as its Best Paper. In this paper, the authors are interested in examining the effectiveness of modeling group dynamics for ‘Group Recommendation’ in Location-Based Social Networks (LBSN). They proposed a novel hierarchical Bayesian model which jointly learns activities and group preferences by using topic models; and performs group recommendation using matrix factorization in a Collaborative Filtering framework. The model allows for group preference learning by capturing location semantics and user-group dynamics and. It also effectively handles data sparsity and cold start recommendation. A major advantage of the modeling framework is that the learned group preferences can be interpreted using latent topics. Empirical experiments on a large LBSN dataset (Gowalla) showed that this model provides more effective group recommendations than the state-of-the-art approaches. Those experiments revealed that the user preferences vary based on their groups, and users tend to exhibit a flair for novelty and exploration as part of a group. Furthermore, the results provide interesting insights into how the user and group preferences differ, and how the user’s behavior influences group’s decisions.

For more details, please refer to the paper at this link:

*Part of this work was done when Sanjay was interning at Intel Labs, Santa Clara, California.

By |September 27th, 2015|News|Comments Off on MCL Research Paper selected as the Best Paper of an ACM SIGSPATIAL Workshop|

MCL Segmentation Research Work to be Presented at ICCV 2015

The segmentation research in our lab made a significant breakthrough these days. The paper “Robust Image Segmentation Using Contour-guided Color Palettes” by Xiang Fu, Chien-Yi Wang, Chen Chen, Changhu Wang and C.-C. Jay Kuo was accepted by ICCV 2015. In this paper, the contour-guided color palette (CCP) is proposed to efficiently integrate contour and color cues of an image. To find representative colors of an image, color samples along long contours between regions, similar in spirit to machine learning methodology that focus on samples near decision boundaries, are collected to achieve an image-dependent color palette. This color palette provides a preliminary segmentation in the spatial domain, which is further fine-tuned by post-processing techniques such as leakage avoidance, fake boundary removal, and small region mergence. While CCP offers an acceptable standalone segmentation result, it can be further integrated into the framework of layered spectral segmentation to produce a more robust segmentation.


For more details, please refer to our paper that will be published soon. The latest code of this paper can be downloaded here. It is written in MATLAB, and has been tested under 64-bit Windows, Linux, and Mac OSX.

By |September 20th, 2015|News|Comments Off on MCL Segmentation Research Work to be Presented at ICCV 2015|

Interview with new MCL member He Ming Zhang

In 2015 Fall semester, MCLab has a new PhD student, He Ming Zhang. She received the B.S. degree in Communication Engineering and M.S degree in , both from Delft University of Technology, Delft, Netherlands. Now we have an interview with her, talking about her background and her thoughts on USC and MCLab.

1. Could you briefly introduce yourself? 

I received my Bachelor of Science in Electrical Engineering at Delft University of Technology (TU Delft). After that, I continued my study at Delft for a master degree in multimedia signal processing. My research experiences include designing protocols for secure signal processing and analyzing algorithms for distributed signal processing.

2. What is your first impression of USC and MCL?

Unlike TU Delft, USC has more diversity in schools and also the students. The first time I walked through the campus, I was impressed by the high density of buildings.

MCL has a really large number of students but Prof. Kuo still manages to work quite close with students. It is amazing that I can meet him at least twice per week. The whole group looks like a big family. People communicate with each other very well.

3.What’s your future expectation for MCL?

I hope I will soon know everyone well and become good friends with them. I desire for a friendly study and research environment where people are inspired by each other. I also hope that I can enjoy the research here and contribute to the field of computer vision.

By |September 14th, 2015|News|Comments Off on Interview with new MCL member He Ming Zhang|
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    Congratulations to two MCL PhD students for passing their defense

Congratulations to two MCL PhD students for passing their defense

Congratulations to Sanjay Purushotham and Pang-Chang (Brian) Lan, who passed their defense last week! Following are their thesis abstracts and they also shared their PhD experiences.
Thesis: Advanced Machine Learning Techniques for Video, Social, and Biomedical Data Analytics (Sanjay Purushotham)
In this thesis, advanced machine learning techniques are developed to tackle challenging problems arising in three Big Data application domains. They are: 1) partial near-duplicate content copy detection and alignment for the multimedia (video) application, 2) personalized single user and group recommender systems for the social media data application, and 3) sparse learning models for identification of discriminative feature interactions for gene expression prediction and cancer stage classification for the biomedical data application. Novel and suitable machine learning algorithms and models are designed to meet the nature of the data in each specific application domain. 

Thesis: Secure Wireless Communications with Side Information: Secrecy Analysis and Unitary Modulation Realization (Brian Lan)
In wireless communication systems such as LTE, information security is protected by symmetric cryptography which assumes that the user and the base station shares the same secret key. But before the setup of the symmetric cryptosystems, the key sharing and authentication processes are vulnerable to eavesdropping. This is referred to as the secure initiation problem. Our work proposes to use physical layer techniques to achieve perfect secrecy without using cryptography, so the secure initiation problem can be solved. In particular, we bring up the concept of having only channel state information (CSI) at the transmitter side but not at the receiver nor the eavesdropper. This concept will be shown beneficial in secrecy comparing to the conventional assumption of full CSI at all terminals. A practical scheme, unitary modulation, is then proposed to exploit this concept. [...]

By |September 6th, 2015|News|Comments Off on Congratulations to two MCL PhD students for passing their defense|