2 citations · 4 across the 7 of their papers we have counts for
7 papers
Weight Block Sparsity: Training, Compilation, and AI Engine Accelerators
Paolo D'Alberto, Taehee Jeong, Akshai Jain +5
Nowadays, increasingly larger Deep Neural Networks (DNNs) are being developed, trained, and utilized. These networks require significant computational resources, putting a strain o…
Entropy Maximization in Sparse Matrix by Vector Multiplication ()
Paolo D'Alberto, Abhishek Jain, Ismail Bustany +2
The peak performance of any SpMV depends primarily on the available memory bandwidth and its effective use. GPUs, ASICs, and new FPGAs have higher and higher bandwidth; however, fo…
Digital Advertising: the Measure of Mobile Visits Lifts
Paolo D'Alberto, Veronica Milenkiy, Fairiz Fi Azizi
Mobile-phone advertising enables marketers to reach customers at a personal level and it enables the measure of costumers reaction by novel approaches, in real time, and at scale.…
Mapping and Matching Algorithms: Data Mining by Adaptive Graphs
Paolo D'Alberto, Veronica Milenkly
Assume we have two bijective functions and with for all and . Every day and in different locations, we see the different…
Multiple-Campaign Ad-Targeting Deployment: Parallel Response Modeling, Calibration and Scoring Without Personal User Information
Paolo D'Alberto
We present a vertical introduction to campaign optimization; that is, the ability to predict the user response to an ad campaign without any users' profiles on average and for each…
A Heterogeneous Accelerated Matrix Multiplication: OpenCL + APU + GPU+ Fast Matrix Multiply
Paolo D'Alberto
As users and developers, we are witnessing the opening of a new computing scenario: the introduction of hybrid processors into a single die, such as an accelerated processing unit…