Fine-grained Private Knowledge Distillation

Knowledge distillation has emerged as a scalable and effective way for privacy-preserving machine learning. One remaining drawback is that it consumes privacy in a model-level (i.e., client-level) manner, every distillation query incurs privacy loss of one client's all records. In order to attain fine-grained privacy accountant and improve utility, this work proposes a model-free reverse $k$-NN labeling method towards record-level private knowledge distillation, where each record is employed for labeling at most $k$ queries. Theoretically, we provide bounds of labeling error rate under the centralized/local/shuffle model of differential privacy (w.r.t. the number of records per query, privacy budgets). Experimentally, we demonstrate that it achieves new state-of-the-art accuracy with one order of magnitude lower of privacy loss. Specifically, on the CIFAR-$10$ dataset, it reaches $82.1\%$ test accuracy with centralized privacy budget $1.0$; on the MNIST/SVHN dataset, it reaches $99.1\%$/$95.6\%$ accuracy respectively with budget $0.1$. It is the first time deep learning with differential privacy achieve comparable accuracy with reasonable data privacy protection (i.e., $\exp(\epsilon)\leq 1.5$). Our code is available at https://github.com/liyuntong9/rknn

HHMF: hidden hierarchical matrix factorization for recommender systems

Abstract(#br)Matrix factorization (MF) is one of the most powerful techniques used in recommender systems. MF models the (user, item) interactions behind historical explicit or implicit ratings. Standard MF does not capture the hierarchical structural correlations, such as publisher and advertiser in advertisement recommender systems, or the taxonomy (e.g., tracks, albums, artists, genres) in music recommender systems. There are a few hierarchical MF approaches, but they require the hierarchical structures to be known beforehand. In this paper, we propose a Hidden Hierarchical Matrix Factorization (HHMF) technique, which learns the hidden hierarchical structure from the user-item rating records. HHMF does not require the prior knowledge of hierarchical structure; hence, as opposed to..

Top-k Context-Aware Tour Recommendations for Groups

Cities offer a large variety of Points of Interest (POI) for leisure, tourism, culture, and entertainment. This offering is exciting and challenging, as it requires people to search for POIs that satisfy their preferences and needs. Finding such places gets tricky as people gather in groups to visit the POIs (e.g., friends, family). Moreover, a group might be interested in visiting more than one place during their gathering (e.g., restaurant, historical site, coffee shop). This task is known to be the orienteering under several constraints (e.g., time, distance, type ordering). Intuitively, the POI preference depends on the group, and on the context (e.g., time of arrival, previously visited POIs in the itinerary). Recent solutions to the problem focus on recommending a single itinerary, aggregating individual preferences to build the group preference, and contextual information does not affect the scheduling process. In this paper, we present a novel approach to the following setting: Given a history of previous group check-ins, a starting POI, and a time budget, find top-k sequences of POIs relevant to the group and context that satisfy the constraints. Our proposed solution consists of two primary steps: training a POI recommender system for groups, and solving the orienteering problem on a candidate set of POIs using Monte Carlo Tree Search. We collected a ground-truth dataset from Foursquare, and show that the proposed approach improves the performance in comparison to a Greedy baseline technique

Data_Sheet_1_Integrated metabolomics and transcriptomics insights on flavonoid biosynthesis of a medicinal functional forage, Agriophyllum squarrosum (L.), based on a common garden trial covering six ecotypes.xlsx

Agriophyllum squarrosum (L.) Moq., well known as sandrice, is an important wild forage in sandy areas and a promising edible and medicinal resource plant with great domestication potential. Previous studies showed flavonoids are one of the most abundant medicinal ingredients in sandrice, whereby isorhamnetin and isorhamnetin-3-glycoside were the top two flavonols with multiple health benefits. However, the molecular regulatory mechanisms of flavonoids in sandrice remain largely unclear. Based on a common garden trial, in this study, an integrated transcriptomic and flavonoids-targeted metabolomic analysis was performed on the vegetative and reproductive periods of six sandrice ecotypes, whose original habitats covered a variety of environmental factor gradients. Multiple linear stepwise regression analysis unveiled that flavonoid accumulation in sandrice was positively correlated with temperature and UVB and negatively affected by precipitation and sunshine duration, respectively. Weighted co-expression network analysis (WGCNA) indicated the bHLH and MYB transcription factor (TF) families might play key roles in sandrice flavonoid biosynthesis regulation. A total of 22,778 differentially expressed genes (DEGs) were identified between ecotype DL and ecotype AEX, the two extremes in most environmental factors, whereby 85 DEGs could be related to known flavonoid biosynthesis pathway. A sandrice flavonoid biosynthesis network embracing the detected 23 flavonoids in this research was constructed. Gene families Plant flavonoid O-methyltransferase (AsPFOMT) and UDP-glucuronosyltransferase (AsUGT78D2) were identified and characterized on the transcriptional level and believed to be synthases of isorhamnetin and isorhamnetin-3-glycoside in sandrice, respectively. A trade-off between biosynthesis of rutin and isorhamnetin was found in the DL ecotype, which might be due to the metabolic flux redirection when facing environmental changes. This research provides valuable information for understanding flavonoid biosynthesis in sandrice at the molecular level and laid the foundation for precise development and utilization of this functional resource forage.</p

Data_Sheet_2_Integrated metabolomics and transcriptomics insights on flavonoid biosynthesis of a medicinal functional forage, Agriophyllum squarrosum (L.), based on a common garden trial covering six ecotypes.docx

Agriophyllum squarrosum (L.) Moq., well known as sandrice, is an important wild forage in sandy areas and a promising edible and medicinal resource plant with great domestication potential. Previous studies showed flavonoids are one of the most abundant medicinal ingredients in sandrice, whereby isorhamnetin and isorhamnetin-3-glycoside were the top two flavonols with multiple health benefits. However, the molecular regulatory mechanisms of flavonoids in sandrice remain largely unclear. Based on a common garden trial, in this study, an integrated transcriptomic and flavonoids-targeted metabolomic analysis was performed on the vegetative and reproductive periods of six sandrice ecotypes, whose original habitats covered a variety of environmental factor gradients. Multiple linear stepwise regression analysis unveiled that flavonoid accumulation in sandrice was positively correlated with temperature and UVB and negatively affected by precipitation and sunshine duration, respectively. Weighted co-expression network analysis (WGCNA) indicated the bHLH and MYB transcription factor (TF) families might play key roles in sandrice flavonoid biosynthesis regulation. A total of 22,778 differentially expressed genes (DEGs) were identified between ecotype DL and ecotype AEX, the two extremes in most environmental factors, whereby 85 DEGs could be related to known flavonoid biosynthesis pathway. A sandrice flavonoid biosynthesis network embracing the detected 23 flavonoids in this research was constructed. Gene families Plant flavonoid O-methyltransferase (AsPFOMT) and UDP-glucuronosyltransferase (AsUGT78D2) were identified and characterized on the transcriptional level and believed to be synthases of isorhamnetin and isorhamnetin-3-glycoside in sandrice, respectively. A trade-off between biosynthesis of rutin and isorhamnetin was found in the DL ecotype, which might be due to the metabolic flux redirection when facing environmental changes. This research provides valuable information for understanding flavonoid biosynthesis in sandrice at the molecular level and laid the foundation for precise development and utilization of this functional resource forage.</p