Data warehouses provide a great deal of opportunities for performing data mining tasks such as classification and clustering. Typically, updates are collected and applied to the data warehouse periodically in a batch mode, e.g., during the night. Then, all patterns derived from the warehouse by some data mining algorithm have to be updated as well. Due to the very large size of the databases, i...

We propose Batch-Expansion Training (BET), a framework for running a batch optimizer on a gradually expanding dataset. As opposed to stochastic approaches, batches do not need to be resampled i.i.d. at every iteration, thus making BET more resource efficient in a distributed setting, and when disk-access is constrained. Moreover, BET can be easily paired with most batch optimizers, does not req...

This paper describes a new method for reducing the error in a classifier. It uses a weight adjustment update, but includes the very simple rule of either adding or subtracting the adjustment, based on whether the data point is currently larger or smaller than the desired value, and on a pointby-point basis. This gives added flexibility to the convergence procedure, where through a series of tra...

Composting is a solid waste treatment process consisting of the biochemical degradation of organic materials. A controlled microbial aerobic decomposition produces stabilized organic materials to be used as soil conditioners or organic fertilizers. The efficiency of this process is strongly temperature-dependent and the key to successful composting lies in the tracking of an appropriate tempera...

Cloud storage introduces many challenges due to the security and integrity threats toward user’s outsourced data. Many auditing protocols have been proposed, but the majority of them could only serve in single cloud environment. This paper proposes an efficient auditing protocol, which supports batch auditing for multiple data files in multi-cloud environment. By utilizing the bilinear map, the...

Cooperative multicast is an effective solution to address the bottleneck problem of single-hop broadcast in wireless networks. By incorporating with the random linear network coding technique, the existing schemes can reduce the retransmission overhead significantly. However, the receivers may incur large decoding delay and complexity due to the batch decoding scheme. In addition, the dependenc...

In industrial manufacturing, most batch processes are inherently multistage/multiphase in nature. To ensure both quality consistency of the manufactured products and safe operation of this kind of batch process, different multivariate statistical process control (MSPC) methods have been proposed in recent years. This paper gives an overview of multistage/multiphase statistical process control m...

Motivated by a real-world problem, we study a novel budgeted optimization problem where the goal is to optimize an unknown function f(·) given a budget by requesting a sequence of samples from the function. In our setting, however, evaluating the function at precisely specified points is not practically possible due to prohibitive costs. Instead, we can only request constrained experiments. A c...

This paper presents a new framework for dealing with two main types of concept drift (sudden and gradual) in labeled data with decision attribute. The learning examples are processed instance by instance. This new framework, called Online Batch Weighted Ensemble, introduces element of incremental processing into a block-based ensemble of classi ers. Its performance was evaluated experimentally ...