By using the proximal mapping and the Barzilai-Borwein step size rule, we derived a new accelerated proximal gradient algorithm to handle such non-smooth objective functions. The numerical examples showed that
This algorithm is referred to as proximal BiO-AIDm and is summarized in Algorithm 1. Specifically, in each outer loop k, we first run T accelerated gradient descent steps with Nesterov’s momentum with initial point [Math Processing Error]yk to minimize [Math Processing Error]g(xk,⋅) and...
The optimization problem described in (3) can be solved efficiently by applying a fast proximal gradient algorithm named accelerated proximal gradient (APG) (Lin et al., 2009), while the discussion on the issue of parameter selection can be found in (Zhou et al., 2010). As stated in the...
a unified proximal gradient (UPG) method with momentum acceleration was proposed for solving the smooth but possibly nonconvex subproblem. This UPG method guarantees global convergence and will automatically reduce to an optimal accelerated gradient method when the smooth function in the objective is con...
2801 A Smoothed Bregman Proximal Gradient Algorithm for Decentralized Nonconvex Optimization 1461 A SOFT CONTRASTIVE LEARNING-BASED PROMPT MODEL FOR FEW-SHOT SENTIMENT ANALYSIS 8613 A SOUND APPROACH: USING LARGE LANGUAGE MODELS TO GENERATE AUDIO DESCRIPTIONS FOR EGOCENTRIC TEXT-AUDIO RETRIEVAL 8645 A SPATI...
Stochastic averaged gradient accelerated (SAGA) algorithm. It stores N gradient vectors. The method maintains an approximation of the global gradient by removing the old local gradient from the overall sum and replacing it with new local gradient. This is called an aggregated gradient method. We co...
Integration with vLLM for accelerated generation in RLHF tasks (--vllm_num_engines). Support RL Dynamic Sampling from DAPO(--dynamic_filtering and --dynamic_filtering_reward_range) Support DeepSpeed AutoTP training (--ds_tensor_parallel_size) Implementation of RingAttention (--ring_attn_size,...
Enable asynchronous training--async_trainwhen the convergence of the RL algorithm meets requirements. Using hybrid engine--colocate_all_modelsand--vllm_enable_sleepand--deepspeed_enable_sleeprather than distributed RLHF when there are enough GPU memory. ...
Examples of algorithms in this category include the following solvers: Singular Value Thresholding (SVT) [20], the Accelerated Proximal Gradient (APG) [19], and the Augmented Lagrange Multiplier (ALM) [18]. All the solvers for the different problem formulations are grouped in Tables 9 and 11...
Accelerated Proximal Gradient (APGa) Oiter(mnmin(mn)), Opre(1/ϵ), Oconv(1/T2) Lin et al. (2009) [19] Full SVD Dual Method (DMa) Oiter(rmn), Opre(1/ϵ), Oconv(1/T2) Lin et al. (2009) [19] Partial SVD Exacted Augmented Lagrangian Method (EALM) Oiter(mnmin(mn)),...