Abstract: A method for performing sparse quantum Fourier transform computation includes defining a set of quantum circuits, each quantum circuit comprising a Hadamard gate and a single frequency rotation operator, said set of quantum circuits being equivalent to a quantum Fourier transform circuit. The method includes constructing a subset of said quantum circuits in a quantum processor, said quantum processor having a quantum representation of a classical distribution loaded into a quantum state of said quantum processor. The method includes executing said subset of said quantum circuits on said quantum state, and performing a measurement in a frequency basis to obtain a frequency distribution corresponding to said quantum state.

Abstract: One embodiment provides a method including: collecting system log files comprising a plurality of log messages representing activity within the system; generating a plurality of message templates by (i) clustering the plurality of messages into groups having similar activity patterns and (ii) generating a message template for each of the groups; identifying message templates of interest and determining the message templates representing actual end-user events as opposed to system events, wherein the determining comprises (i) identifying a seed set of event types that represent known end-user events based upon identifying the event as being known to be initiated by a user and (ii) correlating the event to the known end-user event based upon a time correlation between the known end-user event and the event within the message template of interest.

Abstract: A method for performing sparse quantum Fourier transform computation includes defining a set of quantum circuits, each quantum circuit comprising a Hadamard gate and a single frequency rotation operator, said set of quantum circuits being equivalent to a quantum Fourier transform circuit. The method includes constructing a subset of said quantum circuits in a quantum processor, said quantum processor having a quantum representation of a classical distribution loaded into a quantum state of said quantum processor. The method includes executing said subset of said quantum circuits on said quantum state, and performing a measurement in a frequency basis to obtain a frequency distribution corresponding to said quantum state.

Abstract: One embodiment provides a method including: collecting, from a plurality of collaborative computing systems, system log files comprising a plurality of log messages representing activity within the system, wherein the activity within the system corresponds to system activity and end-user activity; generating a plurality of message templates, each of the plurality of message templates representing an event type by clustering the plurality of messages into groups having similar activity patterns; identifying, from the plurality of message templates, a subset of message templates representing potential end-user events; differentiating end-user events from system events, in the subset of message templates representing potential end-user events, comprising identifying a seed set of event types that represent known end-user events and correlating potential end-user events remaining after identifying the seed set of event types with the known end-user events; and grouping, based upon the differentiating, the event t

Abstract: Memory-augmented neural networks are provided. In various embodiments, an encoder artificial neural network is adapted to receive an input and provide an encoded output based on the input. A plurality of decoder artificial neural networks is provided, each adapted to receive an encoded input and provide an output based on the encoded input. A memory is operatively coupled to the encoder artificial neural network and to the plurality of decoder artificial neural networks. The memory is adapted to store the encoded output of the encoder artificial neural network and provide the encoded input to the plurality of decoder artificial neural networks.

Abstract: One embodiment provides a method including: collecting system log files comprising a plurality of log messages representing activity within the system; generating a plurality of message templates by (i) clustering, using a clustering algorithm, the plurality of messages into groups having similar activity patterns and (ii) generating a message template for each of the groups; identifying message templates of interest, wherein a message template of interest comprises a template that potentially represents end-user events; and determining, within the message templates of interest, the message templates representing actual end-user events as opposed to system events, wherein the determining comprises (i) identifying a seed set of event types that represent known end-user events based upon identifying the event as being known to be initiated by a user and (ii) correlating the event to the known end-user event based upon a time correlation between the known end-user event and the event within the message template

Abstract: One embodiment provides a method including: collecting, from a plurality of collaborative computing systems, system log files comprising a plurality of log messages representing activity within the system, wherein the activity within the system corresponds to system activity and end-user activity; generating a plurality of message templates, each of the plurality of message templates representing an event type by clustering the plurality of messages into groups having similar activity patterns; identifying, from the plurality of message templates, a subset of message templates representing potential end-user events; differentiating end-user events from system events, in the subset of message templates representing potential end-user events, comprising identifying a seed set of event types that represent known end-user events and correlating potential end-user events remaining after identifying the seed set of event types with the known end-user events; and grouping, based upon the differentiating, the event t

Abstract: A method for server allocation in a Web server “farm” is based on limited information regarding future loads to achieve close to the greatest possible revenue based on the assumption that revenue is proportional to the utilization of servers and differentiated by customer class. The method of server allocation uses an approach of “discounting the future”. Specifically, when the policy faces the choice between a guaranteed benefit immediately and a potential benefit in the future, the decision is made by comparing the guaranteed benefit value with a discounted value of the potential future benefit. This discount factor is exponential in the number of time units that it would take a potential benefit to be materialized. The future benefits are discounted because by the time a benefit will be materialized, things might change and the algorithm might decide to make another choice for a potential (even greater) benefit.

Abstract: Disclosed is a method of scanning a data stream in a single pass to obtain uniform data samples from selected intervals. The method comprises randomly selecting elements from the stream for storage in one or more data buckets and, then, randomly selecting multiple samples from the bucket(s). Each sample is associated with a specified interval immediately prior to a selected point in time. There is a balance of probabilities between the selection of elements stored in the bucket and the selection of elements included in the samples so that elements scanned during the specified interval are included in the sample with equal probability. Samples can then be used to estimate the degree of sortedness of the stream, based on counting how many elements in the sequence are the rightmost point of an interval such that majority of the interval's elements are inverted with respect to the interval's rightmost element.

Abstract: Disclosed are embodiments of a method for online analytic processing of queries and, and more particularly, of a method that extends the on-line analytic processing (OLAP) data model to represent data ambiguity, such as imprecision and uncertainty, in data values. Specifically, the embodiments of the method incorporate a statistical model that allows for uncertain measures to be modeled as conditional probabilities. Additionally, an embodiment of the method further identifies natural query properties (e.g., consistency and faithfulness) and uses them to shed light on alternative query semantics. Lastly, an embodiment of the method further introduces an allocation-based approach to the semantics of aggregation queries over such data.

Abstract: A system and method of approximating edit distance for a set of character strings in a database includes producing a representative sketch for each of the character strings; and approximating an edit distance between two selected character strings based only on the representative sketch for each of the selected character strings. The character strings may comprise text, wherein the method further comprises encoding positions of substrings in the text using anchors, wherein the anchors comprise identical substrings occurring in two input character strings at a nearby position. A set of anchors may be used in a correlated manner, wherein character strings with a sufficiently small edit distance are likely to use a same sequence of anchors. The character strings may be substantially non-repetitive. The representative sketch of a first character string is preferably constructed absent knowledge of a second character string. A size of the representative sketch may be constant.

Abstract: A system and method are described for constructing and implementing generic software agents for automated tuning of computer systems and applications. The framework defines the modules and interfaces to allow agents to be created in a modular fashion. The specifics of the target system are captured by adaptors that provide a uniform interface to the target system. Data in the agent is managed by a metric manager, and controller modules implement the desired control algorithms. The modular structure and common interfaces allow for the construction of generic agents that are applicable to a wide variety of target systems, and can use a wide variety of control algorithms.

Abstract: Disclosed is a system, method, and program storage device of aggregating opinions comprising consolidating a plurality of expressed opinions on various dimensions of topics as discrete probability distributions, generating an aggregate opinion as a single point probability distribution by minimizing a sum of weighted divergences between a plurality of the discrete probability distributions, and presenting the aggregate opinion as a Bayesian network, wherein the divergences comprise Kullback-Liebler distance divergences, and wherein the expressed opinions are generated by experts and comprise opinions on sentiments of products and services. Moreover, the aggregate opinion predicts success of the products and services. Furthermore, the experts are arranged in a hierarchy of knowledge, wherein the knowledge comprises the various dimensions of topics for which opinions may be expressed upon.