This paper proposes a new method for approximate string search, specifically candidate generation in spelling error correction, which is a task as follows. Given a misspelled word, the system finds words in a dictionary, which are most “similar” to the misspelled word. The paper proposes a probabilistic approach to the task, which is both accurate and efficient. The approach includes the use of...

We propose a novel model training method for reranking problems. In our proposed approach, named the round-robin duel discrimination (R2D2), model training is done so that all pairs of samples can be distinguished from each other. The loss function of R2D2 for a log-linear model is concave. Therefore we can easily find the global optimum by using a simple parameter estimation method such a grad...

The Evidential regression network (ENet) estimates a continuous target and its predictive uncertainty without costly Bayesian model averaging. However, it is possible that the inaccurately predicted due to gradient shrinkage problem of original loss function ENet, negative log marginal likelihood (NLL) loss. In this paper, objective improve prediction accuracy ENet while maintaining efficient e...

What are the natural loss functions or fitting criteria for binary class probability estimation? This question has a simple answer: so-called “proper scoring rules”, that is, functions that score probability estimates in view of data in a Fisher-consistent manner. Proper scoring rules comprise most loss functions currently in use: log-loss, squared error loss, boosting loss, and as limiting cas...

drying characteristics of green pea (pisum satium) with an initial moisture content of 76% (db) was studied in a fluidized bed dryer assisted by microwave heating. four drying air temperatures (30, 40, 50 and 60ºc) and five microwave powers (180, 360, 540, 720 and 900w) were adopted. several experiments were conducted to obtain data for sample moisture content versus drying time. the results sh...

This report discusses our proposed improvements to Fast Hash Tables (FHT) which we name ’Efficient Hash Table’ (EHT) where ’efficient’ relates to both memory efficiency and lookup performance. The mechanism we use to design the EHT lead to improvements in terms of sram memory requirements by the factor of ten over the FHT. Our results back the theoretical analysis and allow accurate predictions...

In this paper, we propose a joint segmentation and classification framework for sentiment analysis. Existing sentiment classification algorithms typically split a sentence as a word sequence, which does not effectively handle the inconsistent sentiment polarity between a phrase and the words it contains, such as “not bad” and “a great deal of ”. We address this issue by developing a joint segme...

Let f : {0, 1} × {0, 1} → {0, 1} be a 2-party function. For every product distribution μ on {0, 1} × {0, 1}, we show that CCμ0.49(f) = O (( log prt1/8(f) · log log prt1/8(f) )2) , where CCε (f) is the distributional communication complexity of f with error at most ε under the distribution μ and prt1/8(f) is the partition bound of f , as defined by Jain and Klauck [Proc. 25th CCC, 2010]. We also...

Abstract: We introduce a sequential investment strategy, called semi-log-optimal strategy. This strategy is related to the log-optimal portfolio approach, where instead of logarithmic objective function its Taylor series approximation is used. The asymptotic rate of growth is analyzed under the only assumption that the market is stationary and ergodic. The performance of the strategy is compare...

Accurate lifetime prediction of lithium-ion batteries is a great challenge for the researchers and engineers involved in battery applications in electric vehicles and satellites.  In this study, a semi-empirical model is introduced to predict the capacity loss of lithium-ion batteries as a function of charge and discharge cycles, operational time, and temperature. The model parameters are obtai...