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gamma-secretase inhibitors (GSIs) can block NOTCH receptor signaling in vitro and therefore offer an attractive targeted therapy for tumors dependent on deregulated NOTCH activity. To clarify the basis for GSI resistance in T cell acute lymphoblastic leukemia (T-ALL), we studied T-ALL cell lines with constitutive expression of the NOTCH intracellular domain(More)
We propose in this paper the normalized Minimum Error Entropy (NMEE). Following the same rational that lead to the normalized LMS, the weight update adjustment for Minimum Error Entropy (MEE) is constrained by the principle of minimum disturbance. Unexpectedly, we obtained an algorithm that not only is insensitive to the power of the input, but is also(More)
This paper develops a new understanding of mean shift algorithms from an information theoretic perspective. We show that the Gaussian blurring mean shift (GBMS) directly minimizes the Renyi's quadratic entropy of the dataset and hence is unstable by definition. Further, its stable counterpart, the Gaussian mean shift (GMS), minimizes the Renyi's ''cross "(More)
In this paper, we propose a fast and accurate approximation to the information potential of Information Theoretic Learning (ITL) using the Fast Gauss Transform (FGT). We exemplify here the case of the Minimum Error Entropy criterion to train adaptive systems. The FGT reduces the complexity of the estimation from O(N 2) to O(pkN) where p is the order of the(More)
— In this paper, we present a weighted Linde-Buzo-Gray algorithm (WLBG) as a powerful and efficient technique for compressing neural spike data. We compare this technique with the recently proposed Self-Organizing Map with Dynamic Learning (SOM-DL) and the traditional SOM. A significant achievement of WLBG over SOM-DL is a 15dB increase in the SNR of the(More)
— In this paper a clustering algorithm that learns the groups of synchronized spike trains directly from data is proposed. Clustering of spike trains based on the presence of synchronous neural activity is of high relevance in neurophys-iological studies. In this context such activity is thought to be associated with functional structures in the brain. In(More)
In this paper, we propose Minimum Error Entropy with self adjusting step-size (MEE-SAS) as an alternative to the Minimum Error Entropy (MEE) algorithm for training adaptive systems. MEE-SAS has faster speed of convergence as compared to MEE technique for the same misadjustment. We attribute this characteristic to automatic learning rate inherent in MEE-SAS(More)
2 To my parents, friends and teachers 3 ACKNOWLEDGMENTS First and most, I express my sincere gratitude to my Ph.D. advisor Dr. Jose Principe for his encouraging and inspiring style that made possible the completion of this work. dissertation would not have been possible. His philosophy on autonomous thinking and the importance of asking for good questions,(More)
Pancreatic ductal adenocarcinoma (PDA) is a highly lethal disease that is refractory to medical intervention. Notch pathway antagonism has been shown to prevent pancreatic preneoplasia progression in mouse models, but potential benefits in the setting of an established PDA tumor have not been established. We demonstrate that the gamma secretase inhibitor(More)
In this paper we introduce a new cost function called Information Theoretic Mean Shift algorithm to capture the " predominant structure " in the data. We formulate this problem with a cost function which minimizes the entropy of the data subject to the constraint that the Cauchy-Schwartz distance between the new and the original dataset is fixed to some(More)