2,803 research outputs found
Building Machines That Learn and Think Like People
Recent progress in artificial intelligence (AI) has renewed interest in
building systems that learn and think like people. Many advances have come from
using deep neural networks trained end-to-end in tasks such as object
recognition, video games, and board games, achieving performance that equals or
even beats humans in some respects. Despite their biological inspiration and
performance achievements, these systems differ from human intelligence in
crucial ways. We review progress in cognitive science suggesting that truly
human-like learning and thinking machines will have to reach beyond current
engineering trends in both what they learn, and how they learn it.
Specifically, we argue that these machines should (a) build causal models of
the world that support explanation and understanding, rather than merely
solving pattern recognition problems; (b) ground learning in intuitive theories
of physics and psychology, to support and enrich the knowledge that is learned;
and (c) harness compositionality and learning-to-learn to rapidly acquire and
generalize knowledge to new tasks and situations. We suggest concrete
challenges and promising routes towards these goals that can combine the
strengths of recent neural network advances with more structured cognitive
models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary
proposals (until Nov. 22, 2016).
https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar
Effectiveness evaluation of STOL transport operations (phase 2)
A computer simulation program which models a commercial short-haul aircraft operating in the civil air system was developed. The purpose of the program is to evaluate the effect of a given aircraft avionics capability on the ability of the aircraft to perform on-time carrier operations. The program outputs consist primarily of those quantities which can be used to determine direct operating costs. These include: (1) schedule reliability or delays, (2) repairs/replacements, (3) fuel consumption, and (4) cancellations. More comprehensive models of the terminal area environment were added and a simulation of an existing airline operation was conducted to obtain a form of model verification. The capability of the program to provide comparative results (sensitivity analysis) was then demonstrated by modifying the aircraft avionics capability for additional computer simulations
Towards More Data-Aware Application Integration (extended version)
Although most business application data is stored in relational databases,
programming languages and wire formats in integration middleware systems are
not table-centric. Due to costly format conversions, data-shipments and faster
computation, the trend is to "push-down" the integration operations closer to
the storage representation.
We address the alternative case of defining declarative, table-centric
integration semantics within standard integration systems. For that, we replace
the current operator implementations for the well-known Enterprise Integration
Patterns by equivalent "in-memory" table processing, and show a practical
realization in a conventional integration system for a non-reliable,
"data-intensive" messaging example. The results of the runtime analysis show
that table-centric processing is promising already in standard, "single-record"
message routing and transformations, and can potentially excel the message
throughput for "multi-record" table messages.Comment: 18 Pages, extended version of the contribution to British
International Conference on Databases (BICOD), 2015, Edinburgh, Scotlan
Private Multiplicative Weights Beyond Linear Queries
A wide variety of fundamental data analyses in machine learning, such as
linear and logistic regression, require minimizing a convex function defined by
the data. Since the data may contain sensitive information about individuals,
and these analyses can leak that sensitive information, it is important to be
able to solve convex minimization in a privacy-preserving way.
A series of recent results show how to accurately solve a single convex
minimization problem in a differentially private manner. However, the same data
is often analyzed repeatedly, and little is known about solving multiple convex
minimization problems with differential privacy. For simpler data analyses,
such as linear queries, there are remarkable differentially private algorithms
such as the private multiplicative weights mechanism (Hardt and Rothblum, FOCS
2010) that accurately answer exponentially many distinct queries. In this work,
we extend these results to the case of convex minimization and show how to give
accurate and differentially private solutions to *exponentially many* convex
minimization problems on a sensitive dataset
The impact of sound field systems on learning and attention in elementary school classrooms
Purpose: An evaluation of the installation and use of sound field systems (SFS) was carried out to investigate their impact on teaching and learning in elementary school classrooms. Methods: The evaluation included acoustic surveys of classrooms, questionnaire surveys of students and teachers and experimental testing of students with and without the use of SFS. Students ’ perceptions of classroom environments and objective data evaluating change in performance on cognitive and academic assessments with amplification over a six month period are reported. Results: Teachers were positive about the use of SFS in improving children’s listening and attention to verbal instructions. Over time students in amplified classrooms did not differ from those in nonamplified classrooms in their reports of listening conditions, nor did their performance differ in measures of numeracy, reading or spelling. Use of SFS in the classrooms resulted in significantly larger gains in performance in the number of correct items on the nonverbal measure of speed of processing and the measure of listening comprehension. Analysis controlling for classroom acoustics indicated that students ’ listening comprehension score
The Hardness of Embedding Grids and Walls
The dichotomy conjecture for the parameterized embedding problem states that
the problem of deciding whether a given graph from some class of
"pattern graphs" can be embedded into a given graph (that is, is isomorphic
to a subgraph of ) is fixed-parameter tractable if is a class of graphs
of bounded tree width and -complete otherwise.
Towards this conjecture, we prove that the embedding problem is
-complete if is the class of all grids or the class of all walls
GYM: A Multiround Distributed Join Algorithm
Multiround algorithms are now commonly used in distributed data processing systems, yet the extent to which algorithms can benefit from running more rounds is not well understood. This paper answers this question for several rounds for the problem of computing the equijoin of n relations. Given any query Q with width w, intersection width iw, input size IN, output size OUT, and a cluster of machines with M=Omega(IN frac{1}{epsilon}) memory available per machine, where epsilon > 1 and w ge 1 are constants, we show that:
1. Q can be computed in O(n) rounds with O(n(INw + OUT)2/M) communication cost with high probability.
Q can be computed in O(log(n)) rounds with O(n(INmax(w, 3iw) + OUT)2/M) communication cost with high probability.
Intersection width is a new notion we introduce for queries and generalized hypertree decompositions (GHDs) of queries that captures how connected the adjacent components of the GHDs are.
We achieve our first result by introducing a distributed and generalized version of Yannakakis\u27s algorithm, called GYM. GYM takes as input any GHD of Q with width w and depth d, and computes Q in O(d + log(n)) rounds and O(n (INw + OUT)2/M) communication cost. We achieve our second result by showing how to construct GHDs of Q with width max(w, 3iw) and depth O(log(n)). We describe another technique to construct GHDs with longer widths and lower depths, demonstrating other tradeoffs one can make between communication and the number of rounds
Exploring the meaning in meaningful coincidences: an interpretative phenomenological analysis of synchronicity in therapy
Synchronicity experiences (SEs) are defined as psychologically meaningful connections between inner events (e.g. thought, dream or vision) and one or more external events occurring simultaneously or at a future point in time. There has been limited systematic research that has investigated the phenomenology of SEs in therapy. This study aimed to redress this by exploring the process and nature of such experiences from the perspective of the practitioner. Semi-structured face-to-face interviews were conducted with a purposive sample of nine practitioners who reported SEs in their therapeutic sessions (three counsellors, three psychologists and three psychotherapists), and focused on how participants make sense of their experiences of synchronicity in therapy. Interpretative phenomenological analysis was used to identify three superordinate themes: sense of connectedness, therapeutic process, and professional issues. Findings suggest that SEs can serve to strengthen the therapeutic relationship and are perceived as useful harbingers of information about the therapeutic process, as well as being a means of overcoming communication difficulties, as they are seen to provide insights into the client’s experiencing of themselves and others, regardless of whether or not the SE is acknowledged by the client or disclosed by the therapist
Assessing the impact of Laurentide Ice Sheet topography on glacial climate
Simulations of past climates require altered boundary conditions to account
for known shifts in the Earth system. For the Last Glacial Maximum (LGM) and
subsequent deglaciation, the existence of large Northern Hemisphere ice
sheets caused profound changes in surface topography and albedo. While
ice-sheet extent is fairly well known, numerous conflicting reconstructions
of ice-sheet topography suggest that precision in this boundary condition is
lacking. Here we use a high-resolution and oxygen-isotope-enabled
fully coupled global circulation model (GCM) (GISS ModelE2-R), along with
two different reconstructions of the Laurentide Ice Sheet (LIS) that provide
maximum and minimum estimates of LIS elevation, to assess the range of
climate variability in response to uncertainty in this boundary condition.
We present this comparison at two equilibrium time slices: the LGM, when
differences in ice-sheet topography are maximized, and 14 ka, when
differences in maximum ice-sheet height are smaller but still exist.
Overall, we find significant differences in the climate response to LIS
topography, with the larger LIS resulting in enhanced Atlantic Meridional
Overturning Circulation and warmer surface air temperatures, particularly
over northeastern Asia and the North Pacific. These up- and downstream effects
are associated with differences in the development of planetary waves in the
upper atmosphere, with the larger LIS resulting in a weaker trough over
northeastern Asia that leads to the warmer temperatures and decreased albedo
from snow and sea-ice cover. Differences between the 14 ka simulations are
similar in spatial extent but smaller in magnitude, suggesting that climate
is responding primarily to the larger difference in maximum LIS elevation in
the LGM simulations. These results suggest that such uncertainty in
ice-sheet boundary conditions alone may significantly impact the results of
paleoclimate simulations and their ability to successfully simulate past
climates, with implications for estimating climate sensitivity to greenhouse
gas forcing utilizing past climate states
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