Paraphrase Generation with Deep Reinforcement Learning

Automatic generation of paraphrases from a given sentence is an important yet challenging task in natural language processing (NLP), and plays a key role in a number of applications such as question answering, search, and dialogue. In this paper, we present a deep reinforcement learning approach to paraphrase generation. Specifically, we propose a new framework for the task, which consists of a \textit{generator} and an \textit{evaluator}, both of which are learned from data. The generator, built as a sequence-to-sequence learning model, can produce paraphrases given a sentence. The evaluator, constructed as a deep matching model, can judge whether two sentences are paraphrases of each other. The generator is first trained by deep learning and then further fine-tuned by reinforcement learning in which the reward is given by the evaluator. For the learning of the evaluator, we propose two methods based on supervised learning and inverse reinforcement learning respectively, depending on the type of available training data. Empirical study shows that the learned evaluator can guide the generator to produce more accurate paraphrases. Experimental results demonstrate the proposed models (the generators) outperform the state-of-the-art methods in paraphrase generation in both automatic evaluation and human evaluation.Comment: EMNLP 201

Skyrmion-hosting B20-type MnSi films on Si substrates grown by flash lamp annealing

The aim of the current thesis was to investigate the preparation of MnSi film on Si substrates. The preparation process includes room temperature sputtering Mn films with different thicknesses and flash-lamp annealing with different energy density (annealing temperature). Systematic investigations on their structural, electrical, magnetic, and magneto-transport properties were performed. The key findings are summarized below: Thin films with the B20-MnSi phase on Si(100) substrates were fabricated for the first time. They exhibit magnetic skyrmion behaviour. In comparison with Si(111) substrates, Si(100) substrates are more preferred from the practical application point of view. The nucleation of B20-MnSi on Si(100) is believed to be triggered by the fast solid-state phase reaction between Mn and Si via ms-range flash-lamp annealing. Compared with the corresponding bulk material, our films show an increased Curie temperature of around 43 K. The magnetic and transport measurements reveal that skyrmions in B20-MnSi on Si(100) made by sub-seconds solid-state reaction are stable within much broader field and temperature windows than bulk MnSi. The parasitic MnSi1.7 phase can be further minimized or eliminated by optimizing the annealing conditions, the quality of the deposited Mn film, and its interface with the Si substrate. Our work demonstrates a promising route for the fabrication of B20-type transition metal silicides for integrated and/or hybrid spintronic applications on Si(100) wafers, which are more preferable for industry applications. The growth of MnSi films on Si(111) substrates has been widely realized by solid phase epitaxy or molecular beam epitaxy since the lattice mismatch and symmetry fit better. One problem is the parasitic MnSi1.7 phase. By controlling the reaction parameters using strongly non-equilibrium flash lamp annealing, we have achieved full control over the phase formation of Mn-silicides in thin films from single-phase B20-MnSi or MnSi1.7 to mixed phases. The obtained films are highly textured and reveal sharp interfaces to the Si substrate. The obtained B20-MnSi films exhibits a high Curie temperature of 41 K. The skyrmion phase can be stabilized over broad temperature and magnetic field ranges. We propose flash-lamp-annealing-induced transient reaction as a general approach for phase separation in transition-metal silicides and germanides and for growth of B20-type films with enhanced topological stability. By comparing the magnetic properties of MnSi films grown on both Si(111) and Si(100) substrates by ourselves and by others in literature, we found one common feature. It is the increased Curie temperature of around 41-43 K for all MnSi films. It is much higher than 29.5 K for bulk MnSi. We try to understand the puzzling Curie temperature widely reported in MnSi films. We have prepared MnSi films with a large variation regarding their thickness, crystallinity, strain and phase separation. Particularly, polycrystalline MnSi films on Si(100) and textured MnSi films on Si(111), both with different mixture ratio with MnSi1.7 have been grown and systematically characterized. Surprisingly, all obtained MnSi films exhibit a high Curie temperature at around 43 K. The skyrmion phase has also been detected in these films. However, we find no correlation between the increased Curie temperate and the film thickness, strain, lattice volume or the mixture with MnSi1.7. Our work has not provided a conclusive picture for this question, but is rather calling a revisit, especially to the effect by the interface, stoichiometry and point defects. Further studies are essential to understand the B20 transition-metal silicide/germanides films and therefore to utilize them for spintronic applications.:Contents Abstract iii Kurzfassung v 1. Introduction 1 1.1 B20 compounds and magnetic skyrmions 1 1.2 B20 MnSi with magnetic Skyrmions 8 1.2.1 Crystallization process 10 1.2.2 Phase diagram of Mn-Si binary compounds 13 1.2.3 Bulk B20-MnSi 14 1.2.4 B20-MnSi thin film 18 1.2.5 B20-MnSi nanowire 25 1.3 Fast annealing method 27 1.4 Objectives and the structure of the thesis 30 2. Experiment 32 2.1 Sample preparation 32 2.1.1 DC magnetron sputtering 32 2.1.2 Sub-second annealing 35 2.2 Structure characterization: X-ray diffraction 40 2.3 Property characterization 41 2.3.1 Magnetic properties 41 2.3.2 Magneto-transport properties 44 3. B20-MnSi films grown on Si(100) substrates with magnetic skyrmion signature 46 3.1 Introduction 46 3.2 Experiment 47 3.3 Results and Discussions 48 3.4 Conclusions 56 4. Phase selection in Mn-Si alloys by fast solid-state reaction with enhanced skyrmion stability 57 4.1 Introduction 57 4.2 Experiment 59 4.3 Results 61 4.3.1 MnSi and MnSi1.7 phase reaction 61 4.3.2 Magnetic Skyrmion 68 4.3.3 Discussion 76 4.4 Conclusion 78 5. On the Curie temperature of MnSi films 80 5.1 Introduction 80 5.2 Experiment 82 5.3 Results 83 5.4 Conclusion 89 6. Summary and outlook 90 6.1 Summary 90 6.2 Outlook 91 6.2.1 Film thickness effect on formation of (111)-textured B20-MnSi 91 6.2.2 MnSi1.7% influence on Skyrmion stability 96 6.2.3 Preparation of other transition-metal monosilicides and germanides 98 Acknowledgement 99 References 101 Publication list 117 Curriculum Vitae 119 Erklärung 12

Bargaining in the Chinese Leviathan: An Examination on the Steel Industry after China's SOE Reform

This thesis centers on the competitions between enterprises in the steel industry in China after the SOE (state-owned enterprises) reform, which can be viewed as a case for mass economic reforms within Chinese Leviathan. To examine the effect of the SOE reform on the distributional benefits within actors of state-owned and private enterprises, Knight's relative bargaining power theory is served as the theoretic foundation. Ownership, is equally as two other explanatory predictor, labor force proportion and enterprise profit per capita as the operationalization of inputs in gaining asymmetric resource (production capacity quota) for players of enterprises in the steel industry. Empirical results from data collected in field work indicate that (1) ownership matters only when interactive with economic performance and PEs take the advantage of ownership; (2) regardless of ownership, enterprises gain relative bargaining power when they do contribution to the social stability. Qualitative analysis from the interviews in fields also explains the results with cases

Achievements and Future Trends of E-Government Service – Implications from the SARS Outbreak

Rapid advances in technology and the advent of the Internet have redefined public expectation of the government and its services. With the great support from Hong Kong and Singapore government, e-government system has achieved temporary success by offering some everyday services through virtual Internet. During last year’s Severe Acute Respiratory Syndrome (SARS) outbreak, e-governments in Hong Kong and Singapore ensured the proper running of government services despite of massive physical restrictions caused by SARS outbreak. E-government started to show its value through continuous development in the past decade. The idea of “virtual government” implementation had been proved in some extent. In the meantime, SARS outbreak introduced new challenges to e-government in dealing with abrupt events. The paper will present the new trends and dynamics in e-government development enlightened by feedbacks from fighting with SARS outbreak. The paper will also provide assessment for those functional specifications raised under the SARS outbreak

Clustering and Classification with Feature Selection for High-Dimensional Data

In this dissertation, we discuss several methods for clustering and classification with feature selection for high-dimensional data. In the first part, we focus on the problem of biclustering, which is the task of simultaneously clustering the rows and columns of the data matrix into different subgroups such that the rows and columns within a subgroup exhibit similar patterns. We provide a new formulation of the biclustering problem based on the idea of minimizing the empirical clustering risk, and introduce a novel algorithm that alternately applies an adapted version of the k-means clustering algorithm between columns and rows. In the second part, we develop a new classification method based on nearest centroid, using disjoint sets of features. We present a simple algorithm based on adapted k-means clustering that can find the subsets of features used in our method and extend the algorithm to perform feature selection. In the third part, we study the problem of classification with feature selection, where the features are selected iteratively in a supervised way to optimize predictive performance. We propose to use beam search to perform feature selection, which can be viewed as a generalization of forward selection. In all parts of the dissertation, we evaluate and compare the performance of our methods to other related methods on both simulated data and real-world datasets.Doctor of Philosoph

Optimal Shipping Decisions in an Airfreight Forwarding Network

This thesis explores three consolidation problems derived from the daily operations of major international airfreight forwarders. First, we study the freight forwarder's unsplittable shipment planning problem in an airfreight forwarding network where a set of cargo shipments have to be transported to given destinations. We provide mixed integer programming formulations that use piecewise-linear cargo rates and account for volume and weight constraints, flight departure/arrival times, as well as shipment-ready times. After exploring the solution of such models using CPLEX, we devise two solution methodologies to handle large problem sizes. The first is based on Lagrangian relaxation, where the problems decompose into a set of knapsack problems and a set of network flow problems. The second is a local branching heuristic that combines branching ideas and local search. The two approaches show promising results in providing good quality heuristic solutions within reasonable computational times, for difficult and large shipment consolidation problems. Second, we further explore the freight forwarder's shipment planning problem with a different type of discount structure - the system-wide discount. The forwarder's cost associated with one flight depends not only on the quantity of freight assigned to that flight, but also on the total freight assigned to other flights operated by the same carrier. We propose a multi-commodity flow formulation that takes shipment volume and over-declaration into account, and solve it through a Lagrangian relaxation approach. We also model the "double-discount" scheme that incorporates both the common flight-leg discount (the one used in the unsplittable shipment problem) and the system-wide discount offered by cargo airlines. Finally, we focus on palletized loading using unit loading devices (ULDs) with pivots, which is different from what we assumed in the previous two research problems. In the international air cargo business, shipments are usually consolidated into containers; those are the ULDs. A ULD is charged depending on whether the total weight exceeds a certain threshold, called the pivot weight. Shipments are charged the under-pivot rate up to the pivot weight. Additional weight is charged at the over-pivot rate. This scheme is adopted for safety reasons to avoid the ULD overloading. We propose three solution methodologies for the air-cargo consolidation problem under the pivot-weight (ACPW), namely: an exact solution approach based on branch-and-price, a best fit decreasing loading heuristic, and an extended local branching. We found superior computational performance with a combination of the multi-level variables and a relaxation-induced neighborhood search for local branching

A Novel Joint Angle-Range-Velocity Estimation Method for MIMO-OFDM ISAC Systems

Integrated sensing and communications (ISAC) is emerging as a key technique for next-generation wireless systems. In order to expedite the practical implementation of ISAC within pervasive mobile networks, it is essential to equip widely-deployed base stations with radar sensing capabilities. Thus, the utilization of standardized multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) hardware architectures and waveforms becomes pivotal for realizing seamless integration of effective communication and sensing functionalities. In this paper, we introduce a novel joint angle-range-velocity estimation algorithm for the MIMO-OFDM ISAC system. This approach exclusively depends on conventional MIMO-OFDM communication waveforms, which are widely adopted in wireless communications. Specifically, the angle-range-velocity information of potential targets is jointly extracted by utilizing all the received echo signals within a coherent processing interval (CPI). Therefore, the proposed joint estimation algorithm can achieve larger processing gains and higher resolution by fully exploiting echo signals and jointly estimating the angle-range-velocity information. Theoretical analysis for maximum unambiguous range, resolution, and processing gains are provided to verify the advantages of the proposed joint estimation algorithm. Finally, extensive numerical experiments are presented to demonstrate that the proposed joint estimation approach can achieve significantly lower root-mean-square-error (RMSE) of angle/range/velocity estimation for both single-target and multi-target scenarios.Comment: 13 pages, 8 figures, submitted to IEEE Tran

Low-Range-Sidelobe Waveform Design for MIMO-OFDM ISAC Systems

Integrated sensing and communication (ISAC) is a promising technology in future wireless systems owing to its efficient hardware and spectrum utilization. In this paper, we consider a multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) ISAC system and propose a novel waveform design to provide better radar ranging performance by taking range sidelobe suppression into consideration. In specific, we aim to design MIMO-OFDM dual-function waveform to minimize its integrated sidelobe level (ISL) while satisfying the quality of service (QoS) requirements of multi-user communications and the transmit power constraint. To achieve a lower ISL, the symbol-level precoding (SLP) technique is employed to fully exploit the degrees of freedom (DoFs) of the waveform design in both temporal and spatial domains. An efficient algorithm utilizing majorization-minimization (MM) framework is developed to solve the non-convex waveform design problem. Simulation results reveal radar ranging performance improvement and demonstrate the benefits of the proposed SLP-based low-range-sidelobe waveform design in ISAC systems