Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers

Since the recent advent of regulations for data protection (e.g., the General Data Protection Regulation), there has been increasing demand in deleting information learned from sensitive data in pre-trained models without retraining from scratch. The inherent vulnerability of neural networks towards adversarial attacks and unfairness also calls for a robust method to remove or correct information in an instance-wise fashion, while retaining the predictive performance across remaining data. To this end, we consider instance-wise unlearning, of which the goal is to delete information on a set of instances from a pre-trained model, by either misclassifying each instance away from its original prediction or relabeling the instance to a different label. We also propose two methods that reduce forgetting on the remaining data: 1) utilizing adversarial examples to overcome forgetting at the representation-level and 2) leveraging weight importance metrics to pinpoint network parameters guilty of propagating unwanted information. Both methods only require the pre-trained model and data instances to forget, allowing painless application to real-life settings where the entire training set is unavailable. Through extensive experimentation on various image classification benchmarks, we show that our approach effectively preserves knowledge of remaining data while unlearning given instances in both single-task and continual unlearning scenarios.Comment: AAAI 2024 camera ready versio

Peroxocobalt(III) species activates nitriles via a superoxocobalt(II) diradical state

The dioxygenation of nitriles by [CoIII(TBDAP)(O2)]+ (TBDAP = N,N-di-tert-butyl-2,11-diaza[3.3](2,6)-pyridinophane) is investigated using DFT-calculations. The mechanism proposed previously based on experimental observations, which invoked an outer-sphere cycloaddition, was found to be unreasonable. Instead, calculations suggest that an inner-sphere mechanism involving the cleavage of one of the Co???O bonds assisted by substrate uptake is much more likely. The reactively competent species is a triplet consisting of a Co(II)-superoxo functionality, which can undergo O???C bond formation and O???O bond cleavage traversing low energy transition states. The role of the structurally rigid TBDAP ligand is to prevent the participation of the pyridyl ligand in the delocalization of the unpaired electron density

Controlled Regulation of the Nitrile Activation of a Peroxocobalt(III) Complex with Redox-Inactive Lewis Acidic Metals

Redox-inactive metal ions play vital roles in biological O-2 activation and oxidation reactions of various substrates. Recently, we showed a distinct reactivity of a peroxocobalt(III) complex bearing a tetradentate macrocyclic ligand, [Co-III(TBDAP)(O-2)](+) (1) (TBDAP = N,N'-di-tert-butyl-2,11-diaza[3.3](2,6)pyridinophane), toward nitriles that afforded a series of hydroximatocobalt(III) complexes, [Co-III(TBDAP)(R-C(=NO)O)](+) (R = Me (3), Et, and Ph). In this study, we report the effects of redox-inactive metal ions on nitrile activation of 1. In the presence of redox-inactive metal ions such as Zn2+, La3+, Lu3+, and Y3+, the reaction does not form the hydroximatocobalt(III) complex but instead gives peroxyimidatocobalt(III) complexes, [Co-III(TBDAP)(R-C(=NH)O-2)](2+) (R = Me (2) and Ph (2(Ph))). These new intermediates were characterized by various physicochemical methods including X-ray diffraction analysis. The rates of the formation of 2 are found to correlate with the Lewis acidity of the additive metal ions. Moreover, complex 2 was readily converted to 3 by the addition of a base. In the presence of Al3+, Sc3+, or H+, 1 is converted to [Co-III(TBDAP)(O2H)(MeCN)](2+) (4), and further reaction with nitriles did not occur. These results reveal that the reactivity of the peroxocobalt(III) complex 1 in nitrile activation can be regulated by the redox-inactive metal ions and their Lewis acidity. DFT calculations show that the redox-inactive metal ions stabilize the peroxo character of end-on Co-eta(1)-O-2 intermediate through the charge reorganization from a Co-II-superoxo to a Co-III-peroxo intermediate. A complete mechanistic model explaining the role of the Lewis acid is presented

Realization of negative refraction in visible range using vertical hyperbolic metamaterials

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Oxidatively induced reactivity in Rh(iii)-catalyzed 7-azaindole synthesis: insights into the role of the silver additive

A typical synthetic protocol for preparing 7-azaindoles involves the coupling of 2-aminopyridine and alkyne substrates using a Rh(iii)-catalyst. The catalysis requires the assistance of an external Ag+ oxidant that is thought to regenerate the catalyst and increase the turnover efficiency. Density functional theory (DFT) simulations confirm that Ag+ can oxidize various neutral Rh(iii) intermediates encountered at different stages of the catalysis. Among them, the catalytically relevant species is a cationic Rh(iii)-pyridyl(+) complex (2A), which undergoes C-H activation of pyridine and couples an internal alkyne substrate into the pyridyl ligand to form the desired 7-azaindole product. Computations reveal that the oxidation also accelerates the reaction steps, including C-H activation via concerted metalation deprotonation (CMD), 1,2-alkyne insertion, and reductive elimination, thus highlighting the role of Ag+ as a catalytic promoter for the oxidatively induced reactivity of the Rh-catalyst in 7-azaindole synthesis. DFT calculations show that the catalysis is inefficient without invoking an oxidatively induced reaction pathway.11Nsciescopu

Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers

Since the recent advent of regulations for data protection (e.g., the General Data Protection Regulation), there has been increasing demand in deleting information learned from sensitive data in pre-trained models without retraining from scratch. The inherent vulnerability of neural networks towards adversarial attacks and unfairness also calls for a robust method to remove or correct information in an instance-wise fashion, while retaining the predictive performance across remaining data. To this end, we consider instance-wise unlearning, of which the goal is to delete information on a set of instances from a pre-trained model, by either misclassifying each instance away from its original prediction or relabeling the instance to a different label. We also propose two methods that reduce forgetting on the remaining data: 1) utilizing adversarial examples to overcome forgetting at the representation-level and 2) leveraging weight importance metrics to pinpoint network parameters guilty of propagating unwanted information. Both methods only require the pre-trained model and data instances to forget, allowing painless application to real-life settings where the entire training set is unavailable. Through extensive experimentation on various image classification benchmarks, we show that our approach effectively preserves knowledge of remaining data while unlearning given instances in both single-task and continual unlearning scenarios

Site-Selective 1,1-Difunctionalization of Unactivated Alkenes Enabled by Cationic Palladium Catalysis

© 2019 American Chemical Society.A palladium(II)-catalyzed 1,1-difunctionalization of unactivated terminal and internal alkenes via addition of two nucleophiles was developed using a cationic palladium(II) complex. The palladacycle generated in situ as a result of a regioselective addition of a nucleophile to the alkene can readily undergo regioselective β-hydride elimination and migratory insertion with a cationic palladium catalyst. The resulting η3-π-allyl palladium(II) complex is the key intermediate that reacts with a second nucleophile to furnish the desired 1,1-difunctionalization of the alkene. Under the optimized reaction conditions, a wide range of indoles and anilines add to alkene units of 3-butenoic or 4-pentenoic acid derivatives to afford the synthetically useful γ,γ- or δ,δ-difunctionalized products with excellent regiocontrol. Furthermore, by employing internal hydroxyl or acid groups and external carbon nucleophiles, this transformation enables unsymmetric 1,1-difunctionalization to forge challenging and important oxo quaternary carbon centers. Combining experiments and DFT calculations on the mechanism of the reaction is investigated in detai

Bronsted acid catalysis of photosensitized cycloadditions

Catalysis is central to contemporary synthetic chemistry. There has been a recent recognition that the rates of photochemical reactions can be profoundly impacted by the use of Lewis acid catalysts and co-catalysts. Herein, we show that Bronsted acids can also modulate the reactivity of excited-state organic reactions. Bronsted acids dramatically increase the rate of Ru(bpy)(3)(2+)-sensitized [2 + 2] photocycloadditions between C-cinnamoyl imidazoles and a range of electron-rich alkene reaction partners. A combination of experimental and computational studies supports a mechanism in which the Bronsted acid co-catalyst accelerates triplet energy transfer from the excited-state [Ru*(bpy)(3)](2+) chromophore to the Bronsted acid activated C-cinnamoyl imidazole. Computational evidence further suggests the importance of driving force as well as geometrical reorganization, in which the protonation of the imidazole decreases the reorganization penalty during the energy transfer event. © The Royal Society of Chemistry 202

Ttyh1 regulates embryonic neural stem cell properties by enhancing the Notch signaling pathway

Despite growing evidence linking Drosophila melanogaster tweety-homologue 1 (Ttyh1) to normal mammalian brain development and cell proliferation, its exact role has not yet been determined. Here, we show that Ttyh1 is required for the maintenance of neural stem cell (NSC) properties as assessed by neurosphere formation and in vivo analyses of cell localization after in utero electroporation. We find that enhanced Ttyh1-dependent stemness of NSCs is caused by enhanced γ-secretase activity resulting in increased levels of Notch intracellular domain (NICD) production and activation of Notch targets. This is a unique function of Ttyh1 among all other Ttyh family members. Molecular analyses revealed that Ttyh1 binds to the regulator of γ-secretase activity Rer1 in the endoplasmic reticulum and thereby destabilizes Rer1 protein levels. This is the key step for Ttyh1-dependent enhancement of γ-secretase activity, as Rer1 overexpression completely abolishes the effects of Ttyh1 on NSC maintenance. Taken together, these findings indicate that Ttyh1 plays an important role during mammalian brain development by positively regulating the Notch signaling pathway through the downregulation of Rer1

Diastereoselective Rhodium-Catalyzed [(3+2+2)] Carbocyclization Reactions with Tethered Alkynylidenecyclopropanes: Synthesis of the Tremulane Sesquiterpene Natural Products

The development of a diastereoselective intramolecular rhodium-catalyzed [(3+2+2)] carbocyclization reactions of allyl ester-tethered alkynylidenecyclopropanes (ACPs) for the construction of the 5,7,5-tricyclic scaffold of the tremulane sesquiterpene natural products is described. This work illustrates that the stereoelectronic nature of the phosphite ligand is critical for attaining high levels of stereocontrol, which is supported by density functional theory (DFT) studies that indicate the migratory insertion step favors the formation of the cis-diastereoisomer. Consequently, several strategies were devised to access the thermodynamically more stable trans-diastereoisomer for the synthesis of the tremulanes; however, the attempts to either switch the sense of stereocontrol in the carbocyclization reaction or epimerize the C7 stereocenter of the cycloadduct provided only modest improvements. Hence, we elected to highlight the synthetic utility of this strategy with the development of concise and highly efficient syntheses of (+/-)-epi-tremulenolide A, (+/-)-epi-tremulenediol A and (+/-)-epi-ceriponol D.11Nsciescopu