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Certified Robust Models with Slack Control and Large Lipschitz Constants
Despite recent success, state-of-the-art learning-based models remain highly vulnerable to input changes such as adversarial examples. In order to...
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Lipschitz-agnostic, efficient and accurate rendering of implicit surfaces
In this paper, we propose an accurate and controllable rendering process for implicit surfaces with no or unknown analytic Lipschitz constants. Our...
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Invariant Lipschitz Bandits: A Side Observation Approach
Symmetry arises in many optimization and decision-making problems, and has attracted considerable attention from the optimization community: by...
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Theoretical analysis of Adam using hyperparameters close to one without Lipschitz smoothness
Convergence and convergence rate analyses of adaptive methods, such as Adaptive Moment Estimation (Adam) and its variants, have been widely studied...
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Exponential Stability of Impulsive Stochastic Neutral Neural Networks with Lévy Noise Under Non-Lipschitz Conditions
In this paper, the exponential stability issue of stochastic impulsive neutral neural networks driven by Lévy noise is explored. By resorting to the...
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Lipschitz Continuity Retained Binary Neural Network
Relying on the premise that the performance of a binary neural network can be largely restored with eliminated quantization error between...
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Modified projection method and strong convergence theorem for solving variational inequality problems with non-Lipschitz operators
In this paper, we introduce a modified projection method and give a strong convergence theorem for solving variational inequality problems in real...
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Iterative methods for solving monotone variational inclusions without prior knowledge of the Lipschitz constant of the single-valued operator
In this work, we investigate a contraction-type method for solving monotone variational inclusion problems in real Hilbert spaces. We obtain strong...
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A decentralized smoothing quadratic regularization algorithm for composite consensus optimization with non-Lipschitz singularities
Distributed algorithms are receiving renewed attention across multiple disciplines due to the dramatically increasing demand of big data processing....
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PPAD-Complete Pure Approximate Nash Equilibria in Lipschitz Games
Lipschitz games, in which there is a limit \(\lambda \)...
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Event-triggered dynamic output-feedback control for a class of Lipschitz nonlinear systems
This paper investigates the problem of dynamic output-feedback control for a class of Lipschitz nonlinear systems. First, a continuous-time...
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Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks
It is a highly desirable property for deep networks to be robust against small input changes. One popular way to achieve this property is by...
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Adaptive three-term PRP algorithms without gradient Lipschitz continuity condition for nonconvex functions
At present, many conjugate gradient methods with global convergence have been proposed in unconstrained optimization, such as MPRP algorithm proposed...
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A Fast and Robust Photometric Redshift Forecasting Method Using Lipschitz Adaptive Learning Rate
With the recent large astronomical survey experiments using high-resolution cameras and telescopes, there has been a tsunami of astronomical data...
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Steganography from perfect codes on Cayley graphs over Gaussian integers, Eisenstein–Jacobi integers and Lipschitz integers
Steganography is the science of communicating a secret message by hiding it in a cover object. The well known F5 algorithm is based on binary Hamming...
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On semilocal convergence analysis for two-step Newton method under generalized Lipschitz conditions in Banach spaces
In the present paper, we consider the semilocal convergence issue of two-step Newton method for solving nonlinear operator equation in Banach spaces....
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CLIP: Cheap Lipschitz Training of Neural Networks
Despite the large success of deep neural networks (DNN) in recent years, most neural networks still lack mathematical guarantees in terms of...
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LipBaB: Computing Exact Lipschitz Constant of ReLU Networks
The Lipschitz constant of neural networks plays an important role in several contexts of deep learning ranging from robustness certification and...
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The Coupling Effect of Lipschitz Regularization in Neural Networks
We investigate the robustness of feed-forward neural networks when input data are subject to random uncertainties. More specifically, we consider...
