نتایج جستجو برای: nips
تعداد نتایج: 574 فیلتر نتایج به سال:
To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop new methods to generate adversarial examples as well as to develop new ways to defend against them. In this chapter, we describe the Alexey Kurakin, Ian Goodfellow, Samy Bengio Google Brain Yinpeng Dong, Fangzhou Lia...
We provide novel methods for efficient dimensionality reduction in kernel spaces. That is, we provide efficient and explicit randomized maps from “data spaces” into “kernel spaces” of low dimension, which approximately preserve the original kernel values. The constructions are based on observing that such maps can be obtained from Locality-Sensitive Hash (LSH) functions, a primitive developed f...
We used the datasets of the NIPS 2003 challenge on feature selection as part of the practical work of an undergraduate course on feature extraction. The students were provided with a toolkit implemented in Matlab. Part of the course requirements was that they should outperform given baseline methods. The results were beyond expectations: the student matched or exceeded the performance of the be...
We establish an information complexity lower bound of randomized algorithms for simulating underdamped Langevin dynamics. More specifically, we prove that the worst $L^2$ strong error is order $\Omega(\sqrt{d}\, N^{-3/2})$, solving a family $d$-dimensional dynamics, by any algorithm with only $N$ queries to $\nabla U$, driving Brownian motion and its weighted integration, respectively. The matc...
Abstract The analysis workflow of Prompt gamma activation (PGAA) at the Budapest Neutron Centre’s PGAA and NIPS-NORMA facilities, MLZ FRM II station, other centers worldwide relied on use Hypermet-PC spectrometry software ProSpeRo concentration calculation Excel macro. sustained interest our user community amid reduced availability multiple large-scale neutron sources called for more efficient ...
We designed four datasets for the purpose of benchmarking local causal discovery algorithms. These include two “re-simulated” datasets obtained from artificially generated data from models trained with real data and two datasets including real variables intermixed with artificial variables (called probes). There is no time dependency in the samples. We chose applications in marketing, pharmacol...
In this chapter, we describe our question answering system, which was the winning system at the Human–Computer Question Answering (HCQA) Competition at the Thirty-first Annual Conference on Neural Information Processing Systems (NIPS). The competition requires participants to address a factoid question answering task referred to as quiz bowl. To address this task, we use two novel neural networ...
We used the datasets of the NIPS 2003 challenge on feature selection as part of the practical work of an undergraduate course on feature extraction. The students were provided with a toolkit implemented in Matlab. Part of the course requirements was that they should outperform given baseline methods. The results were beyond expectations: the student matched or exceeded the performance of the be...
[1] A. Karpathy. t-SNE visualization of CNN. http://cs.stanford.edu/people/karpathy/ cnnembed/. [2] A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems (NIPS), 2012. [3] O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. ...
In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle course. Top participants were invited to describe their algorithms. In this work, we present eight solutions that used deep reinforcement learning approaches, based on algorithms such as Deep Deterministic Policy Gradi...
نمودار تعداد نتایج جستجو در هر سال
با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید