Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Wild, Cody"'
Autor:
Wild, Cody, Anderson, Jesper
Previous work has demonstrated that MLPs within ReLU Transformers exhibit high levels of sparsity, with many of their activations equal to zero for any given token. We build on that work to more deeply explore how token-level sparsity evolves over th
Externí odkaz:
http://arxiv.org/abs/2407.07848
Autor:
Chen, Xin, Toyer, Sam, Wild, Cody, Emmons, Scott, Fischer, Ian, Lee, Kuang-Huei, Alex, Neel, Wang, Steven H, Luo, Ping, Russell, Stuart, Abbeel, Pieter, Shah, Rohin
Imitation learning often needs a large demonstration set in order to handle the full range of situations that an agent might find itself in during deployment. However, collecting expert demonstrations can be expensive. Recent work in vision, reinforc
Externí odkaz:
http://arxiv.org/abs/2205.07886
Autor:
Shah, Rohin, Wang, Steven H., Wild, Cody, Milani, Stephanie, Kanervisto, Anssi, Goecks, Vinicius G., Waytowich, Nicholas, Watkins-Valls, David, Prakash, Bharat, Mills, Edmund, Garg, Divyansh, Fries, Alexander, Souly, Alexandra, Shern, Chan Jun, del Castillo, Daniel, Lieberum, Tom
We held the first-ever MineRL Benchmark for Agents that Solve Almost-Lifelike Tasks (MineRL BASALT) Competition at the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021). The goal of the competition was to promote researc
Externí odkaz:
http://arxiv.org/abs/2204.07123
Autor:
Shah, Rohin, Wild, Cody, Wang, Steven H., Alex, Neel, Houghton, Brandon, Guss, William, Mohanty, Sharada, Kanervisto, Anssi, Milani, Stephanie, Topin, Nicholay, Abbeel, Pieter, Russell, Stuart, Dragan, Anca
The last decade has seen a significant increase of interest in deep learning research, with many public successes that have demonstrated its potential. As such, these systems are now being incorporated into commercial products. With this comes an add
Externí odkaz:
http://arxiv.org/abs/2107.01969
The learned weights of a neural network have often been considered devoid of scrutable internal structure. In this paper, however, we look for structure in the form of clusterability: how well a network can be divided into groups of neurons with stro
Externí odkaz:
http://arxiv.org/abs/2103.03386
The learned weights of a neural network are often considered devoid of scrutable internal structure. To discern structure in these weights, we introduce a measurable notion of modularity for multi-layer perceptrons (MLPs), and investigate the modular
Externí odkaz:
http://arxiv.org/abs/2003.04881
Deep reinforcement learning (RL) policies are known to be vulnerable to adversarial perturbations to their observations, similar to adversarial examples for classifiers. However, an attacker is not usually able to directly modify another agent's obse
Externí odkaz:
http://arxiv.org/abs/1905.10615
Malware detection is a popular application of Machine Learning for Information Security (ML-Sec), in which an ML classifier is trained to predict whether a given file is malware or benignware. Parameters of this classifier are typically optimized suc
Externí odkaz:
http://arxiv.org/abs/1903.05700
Malicious web content is a serious problem on the Internet today. In this paper we propose a deep learning approach to detecting malevolent web pages. While past work on web content detection has relied on syntactic parsing or on emulation of HTML an
Externí odkaz:
http://arxiv.org/abs/1804.05020
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.