LT4REC:A Lottery Ticket Hypothesis Based Multi-task Practice for Video Recommendation System

Click-through rate prediction (CTR) and post-click conversion rate prediction (CVR) play key roles across all industrial ranking systems, such as recommendation systems, online advertising, and search engines. Different from the extensive research on CTR, there is much less research on CVR estimation, whose main challenge is extreme data sparsity with one or two orders of magnitude reduction in the number of samples than CTR. People try to solve this problem with the paradigm of multi-task learning with the sufficient samples of CTR, but the typical hard sharing method can't effectively solve this problem, because it is difficult to analyze which parts of network components can be shared and which parts are in conflict, i.e., there is a large inaccuracy with artificially designed neurons sharing. In this paper, we model CVR in a brand-new method by adopting the lottery-ticket-hypothesis-based sparse sharing multi-task learning, which can automatically and flexibly learn which neuron weights to be shared without artificial experience. Experiments on the dataset gathered from traffic logs of Tencent video's recommendation system demonstrate that sparse sharing in the CVR model significantly outperforms competitive methods. Due to the nature of weight sparsity in sparse sharing, it can also significantly reduce computational complexity and memory usage which are very important in the industrial recommendation system.Comment: 6 pages,4 figure

High-Resolution, Two-Dimensional Measurement of Dissolved Reactive Phosphorus in Sediments Using the Diffusive Gradients in Thin Films Technique in Combination with a Routine Procedure

Dissolved reactive phosphorus (DRP) is the most available P form in sediments and often directly controls phytoplankton blooms in aquatic systems. In this study, a novel procedure was developed for two-dimensional (2D) measurement of DRP in sediments at a spatial resolution of 0.45 mm using the diffusive gradients in thin films (DGT) technique with a revised high-capacity binding phase (Zr oxide gel). This procedure involves DGT uptake of P in sediments, 2D slicing of the binding gel on a 0.45 × 0.45-mm grid system, elution of P from each gel square with 1 M NaOH, and microcolorimetric determination of DRP in each eluted solution using 384-microwell plates. Measurements of DRP via this procedure were tested in homogeneous solutions and sediments and produced an acceptable error (<20% relative standard deviation) for the analysis once the accumulated mass of P in each gel square reached 1.2 μg cm^–2. This method was successfully applied to produce 2D images of the DRP distribution in sediments with and without the influence of tubificid worm bioturbation, revealing a much more pronounced and localized impact from tubificid worms than that found using a one-dimensional measurement of pore water DRP concentrations at 1-cm resolution