Stability of matrix factorization for collaborative filtering

We study the stability vis a vis adversarial noise of matrix factorization algorithm for matrix completion. In particular, our results include: (I) we bound the gap between the solution matrix of the factorization method and the ground truth in terms of root mean square error; (II) we treat the matrix factorization as a subspace fitting problem and analyze the difference between the solution subspace and the ground truth; (III) we analyze the prediction error of individual users based on the subspace stability. We apply these results to the problem of collaborative filtering under manipulator attack, which leads to useful insights and guidelines for collaborative filtering system design.Comment: ICML201

Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation Extraction

Distant supervision (DS) has been widely used to automatically construct (noisy) labeled data for relation extraction (RE). Given two entities, distant supervision exploits sentences that directly mention them for predicting their semantic relation. We refer to this strategy as 1-hop DS, which unfortunately may not work well for long-tail entities with few supporting sentences. In this paper, we introduce a new strategy named 2-hop DS to enhance distantly supervised RE, based on the observation that there exist a large number of relational tables on the Web which contain entity pairs that share common relations. We refer to such entity pairs as anchors for each other, and collect all sentences that mention the anchor entity pairs of a given target entity pair to help relation prediction. We develop a new neural RE method REDS2 in the multi-instance learning paradigm, which adopts a hierarchical model structure to fuse information respectively from 1-hop DS and 2-hop DS. Extensive experimental results on a benchmark dataset show that REDS2 can consistently outperform various baselines across different settings by a substantial margin

H-Dibaryon from Lattice QCD with Improved Anisotropic Actions

The six quark state(uuddss) called H dibaryon($J^P=0^+$,$S=-2$) has been calculated to study its existence and stability. The simulations are performed in quenched QCD on $8^3 \times 24$ and $16^3 \times 48$ anisotropic lattices with Symanzik improved gauge action and Clover fermion action. The gauge coupling is $\beta=2.0$ and aspect ratio $\xi=a_s/a_t=3.0$. Preliminary results indicate that mass of H dibaryon is 2134(100)Mev on $8^3 \times 24$ lattice and 2167(59)Mev on $16^3 \times 48$ respectively. It seems that the radius of H dibaryon is very large and the finite size effect is very obvious

Method to Predict Crowding Effects by Postprocessing Molecular Dynamics Trajectories: Application to the Flap Dynamics of HIV-1 Protease.

The internal dynamics of proteins inside of cells may be affected by the crowded intracellular environments. Here, we test a novel approach to simulations of crowding, in which simulations in the absence of crowders are postprocessed to predict crowding effects, against the direct approach of simulations in the presence of crowders. The effects of crowding on the flap dynamics of HIV-1 protease predicted by the postprocessing approach are found to agree well with those calculated by the direct approach. The postprocessing approach presents distinct advantages over the direct approach in terms of accuracy and speed and is expected to have broad impact on atomistic simulations of macromolecular crowding

Dynamically Driven Protein Allostery Exhibits Disparate Responses for Fast and Slow Motions

AbstractThere is considerable interest in the dynamic aspect of allosteric action, and in a growing list of proteins allostery has been characterized as being mediated predominantly by a change in dynamics, not a transition in conformation. For considering conformational dynamics, a protein molecule can be simplified into a number of relatively rigid microdomains connected by joints, corresponding to, e.g., communities and edges from a community network analysis. Binding of an allosteric activator strengthens intermicrodomain coupling, thereby quenching fast (e.g., picosecond to nanosecond) local motions but initiating slow (e.g., microsecond to millisecond), cross-microdomain correlated motions that are potentially of functional importance. This scenario explains allosteric effects observed in many unrelated proteins