Compact Personalized Models for Neural Machine Translation

We propose and compare methods for gradient-based domain adaptation of self-attentive neural machine translation models. We demonstrate that a large proportion of model parameters can be frozen during adaptation with minimal or no reduction in translation quality by encouraging structured sparsity in the set of offset tensors during learning via group lasso regularization. We evaluate this technique for both batch and incremental adaptation across multiple data sets and language pairs. Our system architecture - combining a state-of-the-art self-attentive model with compact domain adaptation - provides high quality personalized machine translation that is both space and time efficient.Comment: Published at the 2018 Conference on Empirical Methods in Natural Language Processin

Determination of Minority Carrier Lifetimes Using The Capacitance-Time Technique

Capacitance—Time (C—T) plots were generated using a Micromanipulator model 410 CV system with a Yokogawa 3022 A4 x—Y recorder (with time base activated). MOS capacitors were pulsed instantaneously from accumulation into deep—depletion. The capacitance was then recorded as the samples relaxed back to their equilibrium state (Cmin). The method used to analyze the C—T data was known as a ZERBST analysis. A FORTRAN program was created to handle the differentiating required for the ZERBST plot. Preliminary results indicate that this set—up will accurately determine minority carrier lifetimes

Better word alignments with supervised ITG models

This work investigates supervised word align-ment methods that exploit inversion transduc-tion grammar (ITG) constraints. We con-sider maximum margin and conditional like-lihood objectives, including the presentation of a new normal form grammar for canoni-calizing derivations. Even for non-ITG sen-tence pairs, we show that it is possible learn ITG alignment models by simple relaxations of structured discriminative learning objec-tives. For efficiency, we describe a set of prun-ing techniques that together allow us to align sentences two orders of magnitude faster than naive bitext CKY parsing. Finally, we intro-duce many-to-one block alignment features, which significantly improve our ITG models. Altogether, our method results in the best re-ported AER numbers for Chinese-English and a performance improvement of 1.1 BLEU over GIZA++ alignments.

Fuzz Testing Projects in Massive Courses

ABSTRACT Scaffolded projects with automated feedback are core instructional components of many massive courses. In subjects that include programming, feedback is typically provided by test cases constructed manually by the instructor. This paper explores the effectiveness of fuzz testing, a randomized technique for verifying the behavior of programs. In particular, we apply fuzz testing to identify when a student's solution differs in behavior from a reference implementation by randomly exploring the space of legal inputs to a program. Fuzz testing serves as a useful complement to manually constructed tests. Instructors can concentrate on designing targeted tests that focus attention on specific issues while using fuzz testing for comprehensive error checking. In the first project of a 1,400-student introductory computer science course, fuzz testing caught errors that were missed by a suite of targeted test cases for more than 48% of students. As a result, the students dedicated substantially more effort to mastering the nuances of the assignment

Frame-semantic parsing

Frame semantics is a linguistic theory that has been instantiated for English in the FrameNet lexicon. We solve the problem of frame-semantic parsing using a two-stage statistical model that takes lexical targets (i.e., content words and phrases) in their sentential contexts and predicts frame-semantic structures. Given a target in context, the first stage disambiguates it to a semantic frame. This model uses latent variables and semi-supervised learning to improve frame disambiguation for targets unseen at training time. The second stage finds the target's locally expressed semantic arguments. At inference time, a fast exact dual decomposition algorithm collectively predicts all the arguments of a frame at once in order to respect declaratively stated linguistic constraints, resulting in qualitatively better structures than naïve local predictors. Both components are feature-based and discriminatively trained on a small set of annotated frame-semantic parses. On the SemEval 2007 benchmark data set, the approach, along with a heuristic identifier of frame-evoking targets, outperforms the prior state of the art by significant margins. Additionally, we present experiments on the much larger FrameNet 1.5 data set. We have released our frame-semantic parser as open-source software.United States. Defense Advanced Research Projects Agency (DARPA grant NBCH-1080004)National Science Foundation (U.S.) (NSF grant IIS-0836431)National Science Foundation (U.S.) (NSF grant IIS-0915187)Qatar National Research Fund (NPRP 08-485-1-083

PERANCANGAN SISTEM SCIENCE ( SOCIAL COMMUNITY EDUCATION AND INFORMATION CENTRE ) BERBASIS WEB DI PT. TELKOMSEL SEMARANG

Pelayanan adalah komponen terpenting dalam memberikan layanan berkualitas, dan pelayanan itu sendiri sangat tergantung kepada kualitas kepribadian customer service. Pelayanan yang tulus yang membudaya dalam internal organisasi akan menjadi keunggulan yang menguntungkan perusahaan. Pelayanan itu sendiri sangat tergantung kepada kualitas kepribadian customer service. Semakin mulia dan baik hati seorang customer service, semakin berkualitas dirinya dalam memberikan pelayanan berkualitas kepada pelanggan dan menciptakan interaksi yang memperkuat hubungan pelanggan dengan perusahaan ke dalam loyalitas Beberapa tahun belakangan ini keanekaragaman permasalahan yang ada di PT Telkomsel mengakibatkan citra perusahaan menjadi menurun. Untuk peningkatan kualitas pelayanan kepada pelanggan, kami merancang SCIENCE berbasis Web yang akan memudahkan pihak terkait untuk mendokumentasikan case yang ada pada saat performansi aplikasi pelayanan menurun sehingga kpi (key performance indicator) dapat tercapai dan case dapat di ekskalasi secara cepat ke divisi tertentu, memperoleh informasi terupdate terhadap produk Telkomsel baik broadband maupun promo secara mudah , memudahkan koordinasi troubleshooting pelayanan purna jual, dan mencapai awt (average waiting time) yang ideal. Selain itu di SCIENCE manager divisi terkait juga dapat memperoleh report top complaint permasalahan yang ada, baik di rekan – rekan ctp (customer touch point) , maupun rekan cho (complain handling officer) sehingga bisa mengambil keputusan yang efektif terhadap permasalahan tersebut