On the Pareto Front of Multilingual Neural Machine Translation

In this work, we study how the performance of a given direction changes with its sampling ratio in Multilingual Neural Machine Translation (MNMT). By training over 200 multilingual models with various model sizes, data sizes, and language directions, we find it interesting that the performance of certain translation direction does not always improve with the increase of its weight in the multi-task optimization objective. Accordingly, scalarization method leads to a multitask trade-off front that deviates from the traditional Pareto front when there exists data imbalance in the training corpus, which poses a great challenge to improve the overall performance of all directions. Based on our observations, we propose the Double Power Law to predict the unique performance trade-off front in MNMT, which is robust across various languages, data adequacy, and the number of tasks. Finally, we formulate the sample ratio selection problem in MNMT as an optimization problem based on the Double Power Law. In our experiments, it achieves better performance than temperature searching and gradient manipulation methods with only 1/5 to 1/2 of the total training budget. We release the code at https://github.com/pkunlp-icler/ParetoMNMT for reproduction.Comment: NeurIPS 202

ARGONAUTE PIWI domain and microRNA duplex structure regulate small RNA sorting in Arabidopsis.

Small RNAs (sRNAs) are loaded into ARGONAUTE (AGO) proteins to induce gene silencing. In plants, the 5'-terminal nucleotide is important for sRNA sorting into different AGOs. Here we show that microRNA (miRNA) duplex structure also contributes to miRNA sorting. Base pairing at the 15th nucleotide of a miRNA duplex is important for miRNA sorting in both Arabidopsis AGO1 and AGO2. AGO2 favours miRNA duplexes with no middle mismatches, whereas AGO1 tolerates, or prefers, duplexes with central mismatches. AGO structure modelling and mutational analyses reveal that the QF-V motif within the conserved PIWI domain contributes to recognition of base pairing at the 15th nucleotide of a duplex, while the DDDE catalytic core of AtAGO2 is important for recognition of the central nucleotides. Finally, we rescued the adaxialized phenotype of ago1-12, which is largely due to miR165 loss-of-function, by changing miR165 duplex structure which we predict redirects it to AGO2

Homogeneous Second-Order Descent Framework: A Fast Alternative to Newton-Type Methods

This paper proposes a homogeneous second-order descent framework (HSODF) for nonconvex and convex optimization based on the generalized homogeneous model (GHM). In comparison to the Newton steps, the GHM can be solved by extremal symmetric eigenvalue procedures and thus grant an advantage in ill-conditioned problems. Moreover, GHM extends the ordinary homogeneous model (OHM) to allow adaptiveness in the construction of the aggregated matrix. Consequently, HSODF is able to recover some well-known second-order methods, such as trust-region methods and gradient regularized methods, while maintaining comparable iteration complexity bounds. We also study two specific realizations of HSODF. One is adaptive HSODM, which has a parameter-free $O(\epsilon^{-3/2})$ global complexity bound for nonconvex second-order Lipschitz continuous objective functions. The other one is homotopy HSODM, which is proven to have a global linear rate of convergence without strong convexity. The efficiency of our approach to ill-conditioned and high-dimensional problems is justified by some preliminary numerical results.Comment: improved writin

A Universal Trust-Region Method for Convex and Nonconvex Optimization

This paper presents a universal trust-region method simultaneously incorporating quadratic regularization and the ball constraint. We introduce a novel mechanism to set the parameters in the proposed method that unifies the analysis for convex and nonconvex optimization. Our method exhibits an iteration complexity of $\tilde O(\epsilon^{-3/2})$ to find an approximate second-order stationary point for nonconvex optimization. Meanwhile, the analysis reveals that the universal method attains an $O(\epsilon^{-1/2})$ complexity bound for convex optimization and can be accelerated. These results are complementary to the existing literature as the trust-region method was historically conceived for nonconvex optimization. Finally, we develop an adaptive universal method to address practical implementations. The numerical results show the effectiveness of our method in both nonconvex and convex problems

Synthesis and systematic evaluation of dark resonance energy transfer (DRET)-based library and its application in cell imaging

10.1002/asia.201403257Chemistry - An Asian Chemistry103581-58

The development of a highly photostable and chemically stable zwitterionic near-infrared dye for imaging applications

Chemical Communications51193989-399

Target Identification : A Challenging Step in Forward Chemical Genetics

Investigation of the genetic functions in complex biological systems is a challenging step in recent year. Hence, several valuable and interesting research projects have been developed with novel ideas to find out the unknown functions of genes or proteins. To validate the applicability of their novel ideas, various approaches are built up. To date, the most promising and commonly used approach for discovering the target proteins from biological system using small molecule is well known a forward chemical genetics which is considered to be more convenient than the classical genetics. Although, the forward chemical genetics consists of the three basic components, the target identification is the most challenging step to chemical biology researchers. Hence, the diverse target identification methods have been developed and adopted to disclose the small molecule bound protein. Herein, in this review, we briefly described the first two parts chemical toolbox and screening, and then the target identifications in forward chemical genetics are thoroughly described along with the illustrative real example case study. In the tabular form, the different biological active small molecules which are the successful examples of target identifications are accounted in this research review.22Yothe