246 citations · 640 across the 16 of their papers we have counts for
17 papers
Reward-Free Attacks in Multi-Agent Reinforcement Learning
Ted Fujimoto, Timothy Doster, Adam Attarian +2
We investigate how effective an attacker can be when it only learns from its victim's actions, without access to the victim's reward. In this work, we are motivated by the scenario…
Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction
Garrett B. Goh, Charles Siegel, Abhinav Vishnu +1
With access to large datasets, deep neural networks (DNN) have achieved human-level accuracy in image and speech recognition tasks. However, in chemistry, data is inherently small…
Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models
Garrett B. Goh, Charles Siegel, Abhinav Vishnu +2
In the last few years, we have seen the transformative impact of deep learning in many applications, particularly in speech recognition and computer vision. Inspired by Google's In…
Using Social Media to Predict the Future: A Systematic Literature Review
Lawrence Phillips, Chase Dowling, Kyle Shaffer +2
Social media (SM) data provides a vast record of humanity's everyday thoughts, feelings, and actions at a resolution previously unimaginable. Because user behavior on SM is a refle…
Understanding Cognitive Depletion in Novice NMR Analysts
Lyndsey Franklin, Kyungsik Han, Zhuanyi Huang +2
We present the results of a user study with novice NMR analysts (N=19) involving a gamified simulation of the NMR analysis process. Participants solved randomly generated spectrum…
Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks
Lawrence Phillips, Nathan Hodas
Increasingly, cognitive scientists have demonstrated interest in applying tools from deep learning. One use for deep learning is in language acquisition where it is useful to know…
Cognitive Depletion in the Wild: a Case Study of NMR Spectroscopy Analysis
Lyndsey Franklin, Nathan Hodas
NMR spectroscopy analysis is a detail-oriented analytic feat that typically requires specific domain expertise and hours of concentration. This work presents an ethnographic-style…
Will Break for Productivity: Generalized Symptoms of Cognitive Depletion
Lyndsey Franklin, Kristina Lerman, Nathan Hodas
In this work, we address the symptoms of cognitive depletion as they relate to generalized knowledge workers. We unify previous findings within a single analytical model of cogniti…
Deep Learning for Computational Chemistry
Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu
The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later,…
Mutual information for fitting deep nonlinear models
Jacob S. Hunter, Nathan O. Hodas
Deep nonlinear models pose a challenge for fitting parameters due to lack of knowledge of the hidden layer and the potentially non-affine relation of the initial and observed layer…
Beyond Fine Tuning: A Modular Approach to Learning on Small Data
Ark Anderson, Kyle Shaffer, Artem Yankov +2
In this paper we present a technique to train neural network models on small amounts of data. Current methods for training neural networks on small amounts of rich data typically r…
Adding Semantic Information into Data Models by Learning Domain Expertise from User Interaction
Nathan Oken Hodas, Alex Endert
Interactive visual analytic systems enable users to discover insights from complex data. Users can express and test hypotheses via user interaction, leveraging their domain experti…
Network Weirdness: Exploring the Origins of Network Paradoxes
Farshad Kooti, Nathan O. Hodas, Kristina Lerman
Social networks have many counter-intuitive properties, including the "friendship paradox" that states, on average, your friends have more friends than you do. Recently, a variety…
The Simple Rules of Social Contagion
Nathan O. Hodas, Kristina Lerman
It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming…
Attention and Visibility in an Information Rich World
Nathan O. Hodas, Kristina Lerman
As the rate of content production grows, we must make a staggering number of daily decisions about what information is worth acting on. For any flourishing online social media syst…
Friendship Paradox Redux: Your Friends Are More Interesting Than You
Nathan O. Hodas, Farshad Kooti, Kristina Lerman
Feld's friendship paradox states that "your friends have more friends than you, on average." This paradox arises because extremely popular people, despite being rare, are overrepre…
How Visibility and Divided Attention Constrain Social Contagion
Nathan Oken Hodas, Kristina Lerman
How far and how fast does information spread in social media? Researchers have recently examined a number of factors that affect information diffusion in online social networks, in…