Algebraic model counting unifies many inference tasks on logic formulas by exploiting semirings. Rather than focusing on inference, we consider learning, especially in statistical-relational and neurosymbolic AI, which combine logical, probabilistic...
The strength of modern generative models lies in their ability to be controlled through text-based prompts. Typical "hard" prompts are made from interpretable words and tokens, and must be hand-crafted by humans. There are also "soft" prompts, which...
Based on results of a search for the lepton-family-number-violating decay $K^+ \to π^+μ^+ e^-$ with data collected by experiment E865 at the Alternating Gradient Synchrotron of Brookhaven National Laboratory, we place an upper limit on the branch...
In this paper we propose a novel network adaption method called Differentiable Network Adaption (DNA), which can adapt an existing network to a specific computation budget by adjusting the width and depth in a differentiable manner. The gradient-base...
multiple countries. Adaption focuses on overcoming traditional gradient-based AI training limitations. Its goal is to develop systems that adapt dynamically with
We obtain expressions for the shear and the vorticity tensors of perfect-fluid spacetimes, in terms of the divergence of the Weyl tensor. For such spacetimes, we prove that if the gradient of the energy density is parallel to the velocity, then eithe...
Understanding the vulnerabilities of Large Vision Language Models (LVLMs) to jailbreak attacks is essential for their responsible real-world deployment. Most previous work requires access to model gradients, or is based on human knowledge (prompt eng...
Sentiment Analysis using Stochastic Gradient Descent on 50,000 Movie Reviews Compiled from the IMDB Dataset (⭐ 62)
interactive visualization of 5 popular gradient descent methods with step-by-step illustration and hyperparameter tuning UI (⭐ 1377)
Example demonstrating how gradient descent may be used to solve a linear regression problem (⭐ 550)
Machine unlearning aims to remove the influence of problematic training data after a model has been trained. The primary challenge in machine unlearning is ensuring that the process effectively removes specified data without compromising the model's...
Training latency is critical for the success of numerous intrigued applications ignited by federated learning (FL) over heterogeneous mobile devices. By revolutionarily overlapping local gradient transmission with continuous local computing, FL can r...
Ternary Gradients to Reduce Communication in Distributed Deep Learning (TensorFlow) (⭐ 182)
excessive downhill gradient). The term is also used in video game speedrunning for the fastest achieved time in the game and category. Some sports have world
In the arena of privacy-preserving machine learning, differentially private stochastic gradient descent (DP-SGD) has outstripped the objective perturbation mechanism in popularity and interest. Though unrivaled in versatility, DP-SGD requires a non-t...
The cephalocaudal trend, or cephalocaudal gradient of growth, refers to the pattern of changing spatial proportions over time during growth. One example
We propose NH-TTC, a general method for fast, anticipatory collision avoidance for autonomous robots having arbitrary equations of motions. Our proposed approach exploits implicit differentiation and subgradient descent to locally optimize the non-co...
Decentralized optimization with orthogonality constraints is found widely in scientific computing and data science. Since the orthogonality constraints are nonconvex, it is quite challenging to design efficient algorithms. Existing approaches leverag...
MADDPG is an algorithm in multi-agent reinforcement learning (MARL) that extends the popular single-agent method, DDPG, to multi-agent scenarios. Importantly, DDPG is an algorithm designed for continuous action spaces, where the gradient of the state...
About Along: Along is a teacher-student connection builder provided at no cost by Gradient Learning, a nonprofit organization founded and led by educators who are driven to bring communities, schools, …