TailOPT Experiments

Code for the paper 'Efficient Distributed Optimization under Heavy-Tailed Noise'.

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
book_json		book_json
books		books
data		data
models		models
privacy_analysis		privacy_analysis
utils		utils
README.md		README.md
aggregate_results.py		aggregate_results.py
aggregate_results_script.sh		aggregate_results_script.sh
check_image_extraction.py		check_image_extraction.py
compute_privacy.py		compute_privacy.py
gld23_make.py		gld23_make.py
gldv2_import_parallel.py		gldv2_import_parallel.py
list_datasets.py		list_datasets.py
llm_distribute_gpu.py		llm_distribute_gpu.py
llm_train.py		llm_train.py
main_fed_conf_int.py		main_fed_conf_int.py
main_fed_eff_dataprocess.py		main_fed_eff_dataprocess.py
noniid.sh		noniid.sh
precompute.sh		precompute.sh
precompute_clusters.py		precompute_clusters.py
preprocess_custom_shakespeare.py		preprocess_custom_shakespeare.py
process_books.py		process_books.py
q_llm_bisquare.sh		q_llm_bisquare.sh
run_llm.py		run_llm.py
save_llm.py		save_llm.py
shakespeare.py		shakespeare.py
slurm_confidence.sh		slurm_confidence.sh
slurm_run.sh		slurm_run.sh
synthetic.py		synthetic.py
testing.sh		testing.sh
train_lm.py		train_lm.py
wandb_run_stats.py		wandb_run_stats.py

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