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Found 11 papers, 0 papers with code
Large receptive field strategy and important feature extraction strategy in 3D object detection
To tackle the challenge of expanding the receptive field of a 3D convolutional kernel, we introduce the Dynamic Feature Fusion Module (DFFM).
Distributed Online Convex Optimization with Adversarial Constraints: Reduced Cumulative Constraint Violation Bounds under Slater's Condition
Moreover, if the loss functions are strongly convex, then the network regret bound is reduced to $\mathcal{O}(\log(T))$, and the network cumulative constraint violation bound is reduced to $\mathcal{O}(\sqrt{\log(T)T})$ and $\mathcal{O}(\log(T))$ without and with Slater's condition, respectively.
A Generalized Multi-Modal Fusion Detection Framework
However, due to the sparsity of point clouds, accurate and reliable detection cannot be achieved in specific scenarios.
A Survey of Decision Making in Adversarial Games
Game theory has by now found numerous applications in various fields, including economics, industry, jurisprudence, and artificial intelligence, where each player only cares about its own interest in a noncooperative or cooperative manner, but without obvious malice to other players.
A Survey on Distributed Online Optimization and Game
And the local cost function of each agent is often time-varying in dynamic and even adversarial environments.
On Faster Convergence of Scaled Sign Gradient Descent
For the first two cases, it can be shown that the scaled signGD converges at a linear rate.
Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
A novel algorithm is first proposed and it achieves an $\mathcal{O}(T^{\max\{c, 1-c\}})$ bound for static regret and an $\mathcal{O}(T^{(1-c)/2})$ bound for cumulative constraint violation, where $c\in(0, 1)$ is a user-defined trade-off parameter, and thus has improved performance compared with existing results.
Composition and Application of Current Advanced Driving Assistance System: A Review
Due to the growing awareness of driving safety and the development of sophisticated technologies, advanced driving assistance system (ADAS) has been equipped in more and more vehicles with higher accuracy and lower price.
Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization
This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions.
Resilient Multi-Dimensional Consensus in Adversarial Environment
To this end, this paper first considers a general class of consensus algorithms, where each benign agent computes an "auxiliary point" based on the received values and moves its state toward this point.
Distributed Online Convex Optimization with Time-Varying Coupled Inequality Constraints
Assuming Slater's condition, we show that the algorithm achieves smaller bounds on the constraint violation.
