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Data Poisoning Attacks on Factorization-Based Collaborative Filtering
A data poisoning attack on collaborative filtering systems is introduced and it is demonstrated how a powerful attacker with full knowledge of the learner can generate malicious data so as to maximize his/her malicious objectives, while at the same time mimicking normal user behavior to avoid being detected. Expand
A Theoretical Analysis of NDCG Ranking Measures
A central problem in ranking is to design a measure for evaluation of ranking functions. In this paper we study, from a theoretical perspective, the Normalized Discounted Cumulative Gain (NDCG) whichExpand
A Theoretical Analysis of NDCG Type Ranking Measures
This paper studies, from a theoretical perspective, the widely used Normalized Discounted Cumulative Gain (NDCG)-type ranking measures, and shows that NDCG with logarithmic discount has consistent distinguishability although it converges to the same limit for all ranking functions. Expand
Near-Optimal Design of Experiments via Regret Minimization
We consider computationally tractable methods for the experimental design problem, where k out of n design points of dimension p are selected so that certain optimality criteria are approximatelyExpand
An end-to-end system to identify temporal relation in discharge summaries: 2012 i2b2 challenge
An end-to-end system to identify temporal relation in discharge summaries for the 2012 i2b2 challenge achieved encouraging results, demonstrating the feasibility of the tasks defined by the i 2b2 organizers. Expand
Query understanding enhanced by hierarchical parsing structures
This work extracts a set of syntactic structural features and semantic dependency features from query parse trees to enhance inference model learning and shows that augmenting sequence labeling models with linguistic knowledge can improve query understanding performance in various domains. Expand
Fast and Guaranteed Tensor Decomposition via Sketching
This paper proposes fast and randomized tensor CP decomposition algorithms based on sketching that combine existing whitening and tensor power iterative techniques to obtain the fastest algorithm on both sparse and dense tensors. Expand
DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics
A novel nonparametric Bayesian subspace clustering model that infers both the number of subspaces and the dimension of each subspace from the observed data, which leads to a very efficient deterministic algorithm, DP-space, which retains the non parametric ability under a smallvariance asymptotic analysis. Expand
NCLS: Neural Cross-Lingual Summarization
This work presents an end-to-end CLS framework, which is referred to as Neural Cross-Lingual Summarization (NCLS), and proposes to further improve NCLS by incorporating two related tasks, monolingual summarization and machine translation, into the training process of CLS under multi-task learning. Expand
Dynamic Assortment Optimization with Changing Contextual Information
This paper develops an upper confidence bound (UCB) based policy, an approximation algorithm and an efficient greedy heuristic for assortment optimization, and establishes the regret bound on the order of $\widetilde O(d\sqrt{T})$, where d is the dimension of the feature and O suppresses logarithmic dependence. Expand