Publications

Foundations of social theory

As firms move toward a more disciplined approach to e-business strategic planning, managers are seeking metrics that will help them analyze the success of their e-business inves...

Knowledge and Teaching:Foundations of the New Reform

Lee S. Shulman builds his foundation for teaching reform on an idea of teaching that emphasizes comprehension and reasoning, transformation and reflection. "This emphasis is jus...

Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

Parallel Distributed Processing

What makes people smarter than computers? These volumes by a pioneering neurocomputing group suggest that the answer lies in the massively parallel architecture of the human min...

Advances in prospect theory: Cumulative representation of uncertainty

[57] Sequencing end-labeled DNA with base-specific chemical cleavages

Evaluating the Effectiveness of Large Language Models in Representing Textual Descriptions of Geometry and Spatial Relations (Short Paper)

This research focuses on assessing the ability of large language models (LLMs) in representing geometries and their spatial relations. We utilize LLMs including GPT-2 and BERT t...

Bayesian Data Analysis

I actually own a copy of Harold Jeffreys’s Theory of Probability but have only read small bits of it, most recently over a decade ago to confirm that, indeed, Jeffreys was not t...

Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance

Abstract This paper draws on the social and behavioral sciences in an endeavor to specify the nature and microfoundations of the capabilities necessary to sustain superior enter...

Improved methods for building protein models in electron density maps and the location of errors in these models

Map interpretation remains a critical step in solving the structure of a macromolecule. Errors introduced at this early stage may persist throughout crystallographic refinement ...

Squeeze-and-Excitation Networks

The central building block of convolutional neural networks (CNNs) is the convolution operator, which enables networks to construct informative features by fusing both spatial a...

Aggregated Residual Transformations for Deep Neural Networks

We present a simple, highly modularized network architecture for image classification. Our network is constructed by repeating a building block that aggregates a set of transfor...